Project Conceptualisation

ACIAR Project Title: Smallholder farmer decision-making and technology adoption in southern Lao PDR: opportunities and constraints

Project aim: To improve adoption by smallholder farmers of proven technology and management innovations.The key research questions are:

RQ1. What influences smallholder adoption of proven technologies?

RQ2. How can stakeholder networks be engaged and mobilised to enable smallholder farmers to apply proven technologies?

Project objectives:

1. Identify the drivers and constraints affecting smallholder decision-making with respect to adoption of proven technologies.

2. Develop solution strategies/methods to improve use of proven innovations by farmers.

ACIAR Farming Systems Research

Laos is an agrarian society whose diversified livelihoods are largely underpinned by low-yield subsistence-oriented or semi-commercial rice production and small-scale livestock production (Australian Government, 2014). Lowland and upland rice production often fails to meet annual consumption requirements, with many smallholder farmers exposed to food shortages, hunger and rural poverty. Poorly functioning value chains and poor market access, inadequate product quality, lack of infrastructure and extension, lack of supportive policies and the gendered nature of farming activities all tend to impede farmers’ efforts to improve farming systems and livelihoods (Alexander et al., 2010, Manivong, 2014).

Farming systems in southern Laos vary, according to the biophysical environment (slope, soils, water sources, and rainfall), ethnicity and culture, access to markets and extension, and government policies and priorities (Newby, 2014). The livelihoods of rural families are influenced by a range of internal and external factors moderated by new opportunities or constraints and challenges. Livelihood development is not linear, with the overall trends punctuated by various shocks occurring within and beyond individual households (Newby, 2014). These trends and shocks combine to produce a dynamic environment with farming systems responding rapidly.

Several previous ACIAR projects in southern Laos have introduced technologies and management innovations, built local capacity, developed extension personnel, collaborated with universities and supported food security measures in Laos. New technologies and agricultural practices have been introduced, such as: drought resilient rice and crop varieties; use of appropriate inputs (e.g. varieties, fertilizer, time of planting, etc.); direct seeding of rice to reduce the labour requirement for planting; weed management; efficient irrigated water use; and more appropriate dry-season irrigated crops. Cash crops such as maize and grain legumes (mungbean and/or soybean) have also been introduced to sites with reliable irrigation. Extension systems have been targeted to scale out knowledge-based technologies such as new rice varieties, and livestock and water management techniques. Projects have also been dedicated to developing effective and supportive agricultural policies for rice-based farming systems. Yet despite these positive scientific developments and support networks, smallholder farmers – for reasons yet to be fully determined – are not taking advantage of the opportunities and hence adoption rates are disappointingly low.

For example, the ACIAR project CSE/2009/004 in southern Laos completed in 2014 worked with smallholder farmers to establish opportunities for intensification and/or diversification of rice based farming systems, including: livestock management, alternative dry season crops, rice agronomy, double cropping, and water and nutrient management in wet and dry seasons. While the technologies were considered ‘robust’ or ‘proven’, the research revealed that some farmers were not necessarily ‘market-oriented’ rice producers; rather, they viewed rice production as a platform on which to construct a diversified livelihood strategy using family labour. Opportunities for off- farm income through migration appeared to be transforming rural livelihoods.

The ACIAR project CSE/2006/041 completed in 2014 found that direct seeding of rice in the dry season was more profitable than traditional transplanting, if weeds were managed. Dry season irrigated, maize and legume provided a profitable alternative to irrigated rice in the dry season. However, daily wage rates, output prices and water charges impacted the profitability and adoptability of farming system change, factors often outside the control of individual.

The ACIAR project CSE/2012/077 in 2014 introduced labour saving devices; direct sowing of rice and mechanised harvest and post-harvest drying. Previous research in Northern Laos found that agricultural intensification and heavy mechanisation can produce negative ecological impacts, including increased soil erosion, siltation of the lowlands, gradual soil exhaustion, weed invasion and water pollution (Jobard, 2010). Technical guidance from extension agents on pesticides and cultivars was important in mitigating farmers’ economic risks, pesticide intoxication and environmental degradation. This is an example where current projects can benefit from previous research findings.

Drawing lessons from these previous ACIAR projects in Southern Laos we note that there are many factors affecting smallholder technology adoption that combine to form a highly complex network. Research is needed to map these factors and interrelationships systematically in order to better understand how the technologies interact with the socio-economic supporting conditions. This leads us to our first research question:

RQ1. What influences smallholder adoption of proven technologies?

Adoption of new technologies and innovation

In theory, adoption of technical innovations and interventions provide a mechanism for smallholder farmers to improve household livelihoods, food security and achieve farm productivity goals. Adoption of technical innovations is more likely if the use of inputs increase overall productivity for smallholder farmers without requiring excessive labour demands (Berkhout et al., 2014). When farmers contemplate adoption of new technologies and management innovations their decision making processes are influenced by many factors including; economics, politics, technology, social tradition and the biological environment (Feder et al., 2011, Jobard, 2010, Manivong et al., 2014, Srisopaporn et al., 2015). In a review of adoption by Australian researchers, Pannell et al. (2006) (p1408) found that ‘adoption’ stemmed from a learning process where the farmer collects, integrates and evaluates new information in situations of uncertainty. At least for relatively simple innovations, a farmer’s increased probability of making a good decision that will advance his/her goals occurs through improved knowledge, practice and experiences. Hence the adoption process is continuous, uncertain and repeatedly reviewed, as new information is encountered and circumstances change (Rogers, 2003). In addition, farmers learn and enhance their skills when applying the innovation in situ, with a range of responses to seasonal implementation, e.g., choices in timing, sequencing, intensity, scale. Stages of adoption by farmers have been described by Pannell et al. (2006) to involve: (i) awareness of the problem or opportunity, (ii) non-trial evaluation, (iii) trial evaluation, (iv) adoption, (v) review and modification and (vi) non-adoption or dis-adoption.

Pannell et al. (2006) suggests that in the Australian context and from a farmer’s perspective, relative advantage and trialability are the main characteristics that drive adoption of technologies or practices. Factors influencing the relative advantage include: (i) short term input costs, (ii) yields, (iii) output prices of the innovation or of other activities that it affects, (iv) medium to long term profits, (v) impacts on other parts of the system, (vi) adjustment costs, (vii) impacts on the riskiness of production, (viii) system compatibility, (ix) complexity, (x) government policies, (xi) replacement activity costs, (xii) existing beliefs and values, (xiii) family lifestyle, (xiv) self-image and brand loyalty, (xv) environmental credibility, and (xvi) time scale. Factors influencing the trialability include: (i) degree of divisibility, (ii) operability of results, (iii) time lag, (iv) complexity, (v) cost, (vi) threats to trial, e.g., droughts, diseases, pests, (vii) information applied to decision making, (viii) similarity in behaviour of innovation, (ix) spillover effects from neighbours, and (x) trial performance. In addition, Pannell et al. (2006) mention several key principles influencing adoption. Firstly, communication and education activities will not induce landholders to adopt practices and innovations unless the activities are seen as advancing the landholders’ goals. Secondly, proposed innovations should be good for the environment and economically superior as replacement activities. Thirdly, cost-effective financial incentives may improve the relative ‘attractiveness’ of a desired practice.

International perspectives on factors influencing adoption of new or improved technologies and practices in the Mexican oil palm industry by Aguilar-Gallegos et al. (2015) (p123) also emphasised the complex nature of adoption. They found that adoption was directly related to gains to farmers from higher yields and also information flows between farmers and various supporting institutions. In their research paper, technologies were defined as, “devices such as machines, and inputs such as fertilizers and pesticides, and practices concerning cultivation (planting weeding) and sale of produce (e.g., through traders, or direct sales on local markets) and buy inputs (e.g., from local stores, through contracts with agri-business)”. Several ways of evaluating the uptake of technologies have been propounded. The traditional approach has been to view adoption from a technology-push perspective of ‘good agriculture’ and ‘appropriate innovation’ that has been adopted according to categories of ‘innovators’, ‘early adopters’, ‘late adopters’ and ‘laggards’. Yet other adoption evaluations have been based according to resource endowments, styles of farming and rationales for adopting new or improved technologies and practices (Gilles et al., 2013, Leeuwis and Van den Ban, 2004).

Adoption and dis-adoption may occur and arise with circumstance (Kiptot et al., 2007). Technologies or practices emanating from research or agribusiness can be considered as ‘finished’ or ‘proven’ innovations. These are readymade solutions, however, there is then a requirement that the use and integration by farmers within their farming systems proves valuable (Leeuwis and Van den Ban, 2004). There may be a need for further adaptation to improve fit with the farming system or adjustment of the institutional context in which it will be embedded, or complemented by farmer-generated innovations (Douthwaite et al., 2001, Garb and Friedlander, 2014, Millar and Connell, 2009). The adoption of technologies and practices that are not incremental and easy to fit within existing farming systems rely on changes to institutional frameworks such as rules, regulations, habits, values (Hounkonnou et al., 2012, Klerkx et al., 2010) and requires changes beyond the farming system level, e.g., the supply value chain. For learning and innovation to occur, an understanding of the evolution of farmers’ demand is required in order to flexibly match processes with various innovation support services to achieve ‘best-fit’, and an awareness of sometimes competing interests of actors (Kilelu et al., 2014).

In order to deal with the complexity of agricultural production and food security, Foran et al. (2014) reviewed several frameworks, one of which was the Agricultural Innovation Systems (AIS) framework, that focus on enhancing agricultural research and extension systems. The AIS framework contends with the capacities of individuals and organisations as they translate knowledge into useful social or economic activity in agriculture (Spielman et al., 2009). AIS can be used to understand how agricultural growth is influenced by complex interactions between public, private, and civil society actors, in rapidly changing market and policy regimes (Spielman et al., 2009), and how institutional dynamics across a variety of levels influence agricultural development (Basu and Leeuwis, 2012). AIS is concerned with development pathways and how an innovation platform can support actor-driven system innovation (Mapila et al., 2012, Spielman et al., 2011). Innovations system frameworks use various levels and scales of stakeholder engagement to identify and attempt to alleviate some of the broader structural constraints to local adoption of new knowledge. Engagement with stakeholders, such as farmers and other local actors (e.g., traders, business owners, brokers) will enable identification of local organizational, technical, and institutional opportunities and constraints. These collaborative networks drive more rapid social and economic innovations. AIS frameworks direct efforts into capturing and utilizing different types of knowledge to achieve common goals via an “innovation platform”. Understanding institutional structures (e.g., from government policy through to local cultural norms) with involvement of stakeholders across institutional settings, highlights constraints and opportunities for change, as well as improving the relevance of research (Biggs, 2007, Nederlof et al., 2007). Structural changes to organisational policies, management systems and incentives may be required. Communication, participatory planning, facilitation of teamwork and learning-orientated evaluation, all fostering learning, are valuable tools.

In pursuit of its aim and objectives, this project will use an AIS framework to engage with stakeholders from past and present ACIAR projects and institutions involved in agricultural development in southern Laos. This engagement process will enable the project team to mobilise findings from Research Question 1 to answer a second research question:

RQ2. How can stakeholder networks be engaged and mobilised to enable smallholder farmers to apply proven technologies?