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Complexity-sensitive decision support approaches (CSDSA) have gained prominence in the research for development (R4D) sector. However, limited attention has been given to critically examining the underlying causal assumptions of CSDSAs and their overall effectiveness in navigating complexity and achieving desired outcomes. Scaling Readiness has emerged as a novel CSDSA that is increasingly applied in R4D programs in low- and middle-income countries to improve the scaling of innovation. This study offers theory-based explanations on the extent to which Scaling Readiness supports evidence-based design, implementation and monitoring of scaling strategies in two R4D interventions. The contribution of Scaling Readiness is influenced by various contextual factors, including pre-existing partnerships and established institutional intervention project and performance management practices. The findings underscore the significance of investing in broader institutional impact culture growth. This includes critical evaluation of how funding, incentive, and performance mechanisms enable or constrain evidence-based decision-making and adaptive management at intervention and organizational level towards achieving Sustainable Development Goals.

Cassava's transformation into an industrial raw material necessitates new processing techniques that improve quality while lowering processing costs. Drying has been identified as a major bottleneck in the production of high-quality cassava flour (HQCF) and expansion of its industrial application in Sub-Sahara African. This has triggered efforts towards developing an energy-efficient flash dryer for cassava flour/starch production at a small scale. A scaled-up version of the prototype flash dryer installed at the International Center for Tropical Agriculture (CIAT), Cali, Colombia, was built at the Federal Institute of Industrial Research, Oshodi, (FIIRO), Lagos, Nigeria based on numerical modeling. Excel tools developed by the CGIAR (RTB) scientists were used to design the components and built using locally sourced materials. The automation system of the flash dryer allows for operational flexibility, increased energy efficiency and reduced cost. It features a longer drying tube (22.5 m), a compact and improved heat exchanger, a larger blower for higher air velocity, and a high air/product ratio, thereby optimizing the drying efficiency. The dryer was evaluated with mechanically dewatered cassava mash (wet cake) dried into high quality cassava flour at air temperature of 180 °C and velocity of 13 m/s. The initial moisture content of the wet cake was 47.06 % wb, which was reduced to 9.6 % wb of dried product. Using a capacity of 298.0 kg of wet cake per hour, an output of 186.34 kg of dried product was achieved, resulting in an energy efficiency of 80.8 % and specific energy consumption of 2570 kJ/kg product of final product and 4560 kJ/kg water of evaporated water. These results revealed that the dryer is efficient and suitable for small-scale enterprises. Its use can reduce the production costs and expand the global market opportunity for cassava flour.

This study was designed and carried out to ascertain the situation and perceptions of end users of cassava flash drying equipment in Nigeria with the aim of giving suggestions to policies and approaches for improved technology. Forty-one processing firms were selected and interviewed. Descriptive analyses were used and a logistic regression model was estimated. The results revealed that 49% of the firms stopped using their flash dryers due to the low demand for high-quality cassava flour (HQCF) resulting from the high cost of processing occasioned by an inefficient heat-generating component. The estimated model provides evidence that cost effectiveness (p < 0.05) and energy cost (p < 0.10) are the two major determinants of the continuous usage of flash dryers in the study area. Forty-one percent of the firms indicated willingness to pay for any technical adjustment of their flash dryers, supposing such adjustment would improve on drying and the energy efficiency of the equipment up to 40%. The study recommends that machine fabricators in Nigeria and other African countries should be trained on the production of energy- and cost-efficient small-scale flash dryers. Again, the design and commercialization of flash dryers that can be mounted on mobile trucks for farm-gate processing should be encouraged to facilitate farm-gate processing, thereby reducing postharvest losses resulting from transporting perishable and bulky roots over a long distance.

The international development and social impact evidence community is divided about the use of machine-centered approaches in carrying out systematic reviews and maps. While some researchers argue that machine-centered approaches such as machine learning, artificial intelligence, text mining, automated semantic analysis, and translation bots are superior to human-centered ones, others claim the opposite. We argue that a hybrid approach combining machine and human-centered elements can have higher effectiveness, efficiency, and societal relevance than either approach can achieve alone. We present how combining lexical databases with dictionaries from crowdsourced literature, using full texts instead of titles, abstracts, and keywords. Using metadata sets can significantly improve the current practices of systematic reviews and maps. Since the use of machine-centered approaches in forestry and forestry-related reviews and maps are rare, the gains in effectiveness, efficiency, and relevance can be very high for the evidence base in forestry. We also argue that the benefits from our hybrid approach will increase in time as digital literacy and better ontologies improve globally.

Scaling of innovations is a key requirement for addressing societal challenges in sectors such as health, agriculture, and the environment. Research for development (R4D) programs, projects and other interventions struggle to make particular innovations go to scale. Current conceptualizations of scaling are often too simplistic; more systemic and multidimensional perspectives, frameworks and measures are needed. There is a gap between new complexity-aware theories and perspectives on innovation, and tools and approaches that can improve strategic and operational decision-making in R4D interventions that aim to scale innovations. This paper aims to bridge that gap by developing the key concepts and measures of Scaling Readiness. Scaling Readiness is an approach that encourages critical reflection on how ready innovations are for scaling and what appropriate actions could accelerate or enhance scaling. Scaling Readiness provides action-oriented support for (1) characterizing the innovation and innovation system; (2) diagnosing the current readiness and use of innovations as a proxy for their readiness to scale; (3) developing strategy to overcome bottlenecks for scaling; (4) facilitating and negotiating multi-stakeholder innovation and scaling processes; and (5) navigating and monitoring the implementation process to allow for adaptive management. Scaling Readiness has the potential to support evidence-based scaling strategy design, implementation and monitoring, and – if applied across multiple interventions – can be used to manage a portfolio of innovation and scaling investments.

Multi-stakeholder platforms have become mainstream in projects, programmes and policy interventions aiming to improve innovation and livelihoods systems, i.e. research for development interventions in low- and middle-income contexts. However, the evidence for multistakeholder platforms’ contribution to the performance of research for development interventions and their added value is not compelling. This paper focuses on stakeholder participation as one of the channels for multi-stakeholder platforms’ contribution to the performance of research for development interventions, i.e. stakeholder participation. It uses a quantitative approach and utilizes descriptive statistics and ARIMA models. It shows that, in three Ugandan multi-stakeholder platform cases studied, participation increased both in nominal and in unique terms. Moreover, participation was rather cyclical and fluctuated during the implementation of the research for development interventions. The study also shows that, in addition to locational and intervention factors such as type of the area along a rural–urban gradient targeted by the intervention and human resources provided for multi-stakeholder platform implementation, temporal elements such as phases of research for development intervention objectives and the innovation development process play significant roles in influencing participation. The study concludes that contribution of multi-stakeholder platforms to the performance of research for development projects, programs, policies and other initiatives is constrained by locational and temporal context and conditional on the participation requirements of the objectives pursued by research for development intervention.