For almost eight decades, productivity in the United States agricultural sector has substantially increased, in large extent due to the adoption of technological innovations. Despite the increased utilization of technology, questions remain regarding which producers are more likely to adopt a greater number of technological innovations. This research seeks to understand how commodity diversification strategies, farm characteristics, producer perceptions of risk, conservation, information sources, climate adaptation, and producer demographic characteristics are associated with technology adoption among beef cattle producers in the Southeast United States. Utilizing data from an online survey and an Ordered Probit model, we show that beef cattle producers who also produce fruit have an increased probability of adopting a greater number of technologies. The opposite effect is found for other commodities such as vegetables, row crops, and other livestock. Policy recommendations are also discussed.

Ensuring energy access for rural households is crucial for global sustainable development. Technologies like liquefied petroleum gas, biogas, and efficient cookers are touted as solutions, yet their adoption remains limited despite their potential health, economic, and environmental benefits. We conducted a meta-analysis of 50 studies in developing countries, integrating contextual factors to explore gender and other determinants impacting rural energy transition. Our findings underscore socioeconomic status, social capital, environmental concerns, and gender dynamics as pivotal factors. Notably, women's involvement boosts adoption rates by 7.90 per cent, yet cultural barriers often sideline them from these processes. Thus, our recommendations stress addressing women's roles as energy technology users to foster inclusive energy transitions.

The Eastern Gangetic Plains are a densely populated region of South Asia with comparatively low productivity yet a strong potential to intensify production to meet growing food demands. Conservation agriculture-based sustainable intensification (CASI) has gained academic and policy traction in the region, yet despite considerable promotional activities, uptake remains limited. Based on emerging evidence delving beyond a binary classification of adoption, this qualitative study seeks to explore the experiences and perspectives of smallholder farmers who express positive sentiments about CASI, yet have not progressed to (autonomous) adoption. After thematic coding of semi-structured interviews with 44 experimenting farmers and 38 interested non-users, ten common themes emerged that explain why farmers stagnate in their adoption process. Seven of the ten themes were non-specific to CASI and would constraint promotion and uptake of any agri-system change, highlighting the need for contextual clarity when promoting practice changes in smallholder systems. We summaries this to propose the ‘four T's’ that are required to be addressed to enable agricultural change in smallholder systems: Targeting; Training; Targeted incentives; and Time. Through this more nuanced evaluation approach, we argue the need for a stronger focus on enabling environments rather than technological performance evaluations generically, if promotional efforts are to be successful and emerging sustainable intensification technologies are to be adopted by smallholder farmers.

This paper studies the impact of technological progress on unemployment in a search-matching model with heterogeneous multiworker firms. In the model, some firms continue to reap rewards from new technologies over time and contribute to job creation, while other firms obsolesce and reduce their employment. Thus, the model captures an endogenous change in the aggregate composition of firms (the firm-composition effect). Considering this effect along with the two canonical effects—the capitalization and creative-destruction effects—I examine the importance of each through a simulation. The results show that the firm-composition effect explains almost all the variation in unemployment in the model, mainly through shrinking the number of obsolescing firms relative to surviving firms and increasing the aggregate technology adoption rate when technology progresses rapidly.

Integrating farmers’ preferences into the breeding and dissemination of new genotypes is a effective approach to enhance their successful adoption by farmers. In the case of sweet potato, a staple crop in many parts of West Africa, there is a need for more research on the selection criteria used by farmers when choosing which varieties to grow. This study aims to highlight farmers’ selection criteria for sweet potato varieties in the main production areas in Benin. A total of 480 farmers from the top three sweet potato production areas were surveyed. The relative importance of various traits for sweet potato farmers was evaluated using best-worst scaling methods. Latent class analysis was applied to find groups of farmers with similar preferences. Best-Worst Scaling analysis revealed that high root yield, root size, marketability, and early maturing were the most important variety selection criteria. Latent class analysis revealed three farmers’ groups referred to as ‘Yield potential’, ‘Market value’, and ‘Plant resilience’ classes. ‘Yield potential’ farmers were more likely to be from Atlantique and Alibori departments; they significantly committed more acreage to sweet potato production. The ‘Market value’ farmers highlighted the variety of root size and commercial value as the main selection criteria and consisted of farmers with primary education levels from the Ouémé department. ‘Plant resilience’ refers to a group of Alibori farmers who prioritize environmental issues and primarily grow sweet potatoes for self-consumption. Our findings shed light on farmers’ preferences and suggested that heterogeneity in sweet potato selection criteria was highly influenced by various socio-economic factors and location.

Low and slow adoption of innovative technologies among smallholder farmers in Tunisia is a key agricultural development problem partly related to the existing technology transfer approach used in the country. The objective of this study is to analyse how to design innovative technology transfer strategies more effective in terms of increasing female and male farmers’ adoption of an improved barley variety, ‘Kounouz’, for small ruminant nutrition. A randomised controlled trial method was used with farmers in Tunisia to implement four extension treatments and to evaluate their effects on adoption of Kounouz. Difference-in-difference estimates showed that intensive agricultural trainings can significantly improve adoption of Kounouz. Technical trainings combined with economic and organisational training and female empowerment courses resulted in a higher adoption rate. This finding has important policy implications, because it suggests that ensuring more widespread and equitable adoption of improved technologies may not require changes in the research system, but rather introduction measures that ensure better access for women to gender-sensitive extension programmes given their positive impacts on technology adoption of the household.

The development of transformative technologies for mitigating our global environmental and technological challenges will require significant innovation in the design, development, and manufacturing of advanced materials and chemicals. To achieve this innovation faster than what is possible by traditional human intuition-guided scientific methods, we must transition to a materials informatics-centered paradigm, in which synergies between data science, materials science, and artificial intelligence are leveraged to enable transformative, data-driven discoveries faster than ever before through the use of predictive models and digital twins. While materials informatics is experiencing rapidly increasing use across the materials and chemicals industries, broad adoption is hindered by barriers such as skill gaps, cultural resistance, and data sparsity. We discuss the importance of materials informatics for accelerating technological innovation, describe current barriers and examples of good practices, and offer suggestions for how researchers, funding agencies, and educational institutions can help accelerate the adoption of urgently needed informatics-based toolsets for science in the 21st century.

Bolivia has disseminated several improved technologies in the rice sector, but the average rice productivity in the country is far below the average trend in Latin America in recent years. Although the economic literature has highlighted the role of agricultural technology adoption in increasing agricultural productivity, gaps remain in understanding how rice growers are deciding to adopt and benefit from available improved rice technologies. Most previous adoption studies have evaluated the uptake of individual technologies without paying attention to the complementarities that alternative improved rice technologies may offer to farmers who face multiple marketing and production needs. This study uses data from a nationally representative sample of Bolivian rice growers to analyze farmers' joint decisions in adopting complementary agricultural technologies controlling for potential correlations across these decisions, as well as the extent of adoption of these practices. Evidence suggests that the decisions on multiple technology adoption are closely related, with common factors affecting both adoption and the extent of adoption. Furthermore, there is a need to better target resource-poor farmers, improve information-diffusion channels on agricultural practices, and better use existing farmers' organizations to enhance rice technology adoption.

Recently, Penn World Tables include new data that enable calculation of total factor productivity in addition to output for a large set of countries. We use these new data to examine convergence and divergence across countries by applying a new approach, which differentiates between the dynamics of output and of productivity. Our empirical results lead to two main new contributions to the literature. The first is on the interpretation of “β-convergence” in “growth regressions.” It means that output per worker in each country converges to productivity but does not imply convergence across countries, since productivity tends to diverge from the global frontier. The second contribution is to the literature, which finds that income gaps across countries are due mainly to differential technology adoption. This paper shows that the gaps in technology are not only large but keep growing over time.

This study measures the effect of text message receipt on behavioral change by Ecuadorean blackberry farmers. We examine whether text messages affect knowledge about specific technologies or serve as reminders to farmers to employ practices as part of their crop management strategy. Drawing from well-known theories of behavioral change, we identify pathways relevant to technology adoption. We then describe results from a randomized experiment and measure the impact of the intervention through these pathways. Results suggest that in the blackberry context, timely text messages remind farmers about recommended practices and increase adoption. Effects on knowledge enhancement are not significant.

This paper examines ex-ante impacts of two policy interventions that improve productivity of local-breed cows through artificial insemination (AI) and producers’ access to distant markets through a dairy market hub. The majority of cattle in Kilosa district in Tanzania are local low productivity breeds kept by smallholders and agro-pastoralists. Milk production is seasonal, which constrains producers’ access to distant urban markets, constrains producers’ incomes and restricts profitability in dairy processing. We developed and evaluated an integrated system dynamics (SD) simulation model that captures many relevant feedbacks between the biological dynamics of dairy cattle production, the economics of milk market access, and the impacts of rainfall as an environmental factor. Our analysis indicated that in the short (1 year) and medium (5-year) term, policy interventions have a negative effect on producers’ income due to high AI costs. However, in the long term (5+ years), producers’ income from dairy cattle activities markedly increases (by, on average, 7% per year). The results show the potential for upgrading the smallholder dairy value chain in Kilosa, but achievement of this result may require financial support to producers in the initial stages (first 5 years) of the interventions, particularly to offset AI costs, as well as additional consideration of post-farm value chain costs. Furthermore, institutional aspects of dairy market hub have substantial effects on trade-offs amongst performance measures (e.g. higher profit vs. milk consumption at producer's household) with gain in cumulative profit coming at the expense of a proportional and substantial reduction in home milk consumption.

In the first quarter of the new millennium, the immersive technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) are only a few steps away from becoming the mainstream tools within the design industry. This study investigated the internal and external barriers of technology adoption within design-oriented businesses. A mixed method was used to collect and analyze the data from the employees of a large design firm. This research confirmed that external barriers such as funding, technical support, training, and business strategy that exist at the organizational level are interrelated with the internal barriers such as designers’ and managers’ perception and attitude toward the new technologies. The managerial applications were discussed later and the directions for future research were provided.

Although, the knowledge management (KM)-culture research has helped to validate the importance of cultural values for companies' KM initiatives and provided insights into some important values, it still lacks frameworks and analysis outlining how specific types of cultural values might relate to Knowledge Management system (KMS) adoption and subsequent outcomes. In this paper, we provide a three-dimensional framework to help managers articulate how culture affects their unit's ability to create, transfer, and apply knowledge through KMS use. To illustrate the application of the framework, we also present an exploratory case study we have performed in an international organization in the area of development assistance and capacity development.

The role of identity in older adults’ decision-making about assistive technology adoption has been suggested but not fully explored. This scoping review was conducted to understand better how older adults’ self-image and their desire to maintain this influence their decision-making processes regarding assistive technology adoption. Using the five-stage scoping review framework by Arksey and O'Malley, a total of 416 search combinations were run across nine databases, resulting in a final yield of 49 articles. From these 49 articles, five themes emerged: (a) resisting the negative reality of an ageing and/or disabled identity; (b) independence and control are key; (c) the aesthetic dimension of usability; (d) assistive technology as a last resort; and (e) privacy versus pragmatics. The findings highlight the importance of older adults’ desire to portray an identity consistent with independence, self-reliance and competence, and how this desire directly impacts their assistive technology decision-making adoption patterns. These findings aim to support the adoption of assistive technologies by older adults to facilitate engagement in meaningful activities, enable social participation within the community, and promote health and wellbeing in later life.

If the United Nations Sustainable Development Goals are to be achieved, African smallholder farmers will need to embrace new technologies such as conservation agriculture (CA) in order to increase both their productivity and sustainability. Yet farmers have been slow to embrace CA and when they have, they are inclined to do so at limited intensities. Current investigations tend to apply binary frameworks that classify all utilizations as ‘adoption’, and do not consider in depth the farmer perspectives and contextual realities that affect farmer decision-making on the intensity of use. We analyze 57 in-depth, semi-structured interviews with farmers who implement CA to understand why they tend to do so at limited intensities and what is required to intensify their CA activities, both for them and others within their communities. While most farmers reported substantial yield benefits from using CA, this was mainly related to input intensification (particularly herbicides) and was limited by constrained financial resources. Overall, the intensity of CA utilization was constrained due to farmer-identified constraints across their physical, financial, human and informational resources. Because of this, stagnation at low intensities of CA utilization was common, reflecting the assumed transformational adoption pathway for CA and the focus on binary adoption, as opposed to modification and the broader utilization process. To overcome this, we propose a more nuanced transitional approach focused on the intensification of four broader principles of CA over time [i.e., (1) strategic tillage, (2) soil protection, (3) crop diversification and (4) input management] as opposed to the strict packaging of CA practices. Such a change in approach will foster increased positive perceptions within the community and allow farmers to locally adapt CA to build their own way toward complete CA utilization and with less need for subsidization.

New technologies can aid the success of conservation outcomes. Technology alone will not however guarantee conservation success; this hinges on user adoption. Hence, there is a need to understand users’ adoption decisions and how to account for these to streamline the introduction of new technologies. Wildlife law enforcement rangers constitute a key end-user group for conservation technologies, and although some studies have focused on ranger experiences, and on the impacts of policing technologies on crime rates, few have addressed technology adoption among law enforcement personnel, and none among rangers. To address this gap we conducted a case study focused on a new technology called the Protection Assistant for Wildlife Security (PAWS), which was developed to deter poaching by improving the deployment of wildlife law enforcement ranger foot patrols. We evaluated the impacts of an educational programme on the willingness of Indonesia-based rangers to adopt the tool. Following the programme, rangers reported high levels of willingness to adopt PAWS. Furthermore, the more engaged rangers were in the programme, the more useful and easy to use they perceived PAWS to be, and the stronger their adoption intentions. In contrast, rangers who were more resistant to technology from the outset were less engaged in the programme, highlighting the importance of identifying and addressing sources of resistance. Overall, the findings of this case study stress the significance of accounting for and educating end users in disseminating conservation technologies, reinforcing the importance of accounting for human dimensions of conservation.

Sustainable intensification of African farming systems has been high on the agenda of research and development programs for decades. System innovations such as integrated soil fertility management (ISFM) and conservation agriculture have been proposed to tackle the complex challenges farmers face. In this study, we assess how different factors at the plot, farm and institutional level can influence the adoption of ISFM. We employed a stratified sampling approach to randomly select 285 and 300 farmers in Tamale, northern Ghana and Kakamega County, western Kenya, respectively. These two locations were selected to understand the underlying reasons for their divergent adoption levels. Ordinal regression models were used to identify determinants of adoption. In Tamale, adoption rates of ISFM are much lower than in Kakamega. Only 3% of the farmers fully adopted the recommended practices compared with 36% in Kakamega. The low availability of improved seeds is a major reason for the lower uptake of the complete ISFM paradigm in Tamale. The econometric analysis revealed that plot level variables such as soil carbon, soil texture, slope and plot area had a significant effect on the number of adopted ISFM components at both locations. Moreover, family labor availability is also an important factor. Other farm and household characteristics, such as off-farm occupation, livestock ownership, and membership in associations, matter for Kakamega only. Key policy recommendations include promotion of locally available organic resources and improved access to improved seeds in Tamale.

Most papers studying the impacts of technology adoption on income trajectories assume that firms adopt frontier technologies when available. If these technologies are skill intensive, less-developed economies may fail in successfully implementing them and may become trapped in a low-growth equilibrium. Within a Schumpeterian growth model, we show that differences in adoption barriers and incentives to the accumulation of skills produce differences in the technology level that is optimal to adopt. If the economy is not overly distorted, copying nonfrontier technologies helps compensating for the scarcity of skills and increases the likelihood of copying frontier technologies in the long run. If distortions are significant, it may be optimal to copy less-advanced technologies even in the long run. If adoption is not a skill-intensive activity, then copying frontier technologies is always optimal; all economies achieve a high-growth equilibrium and only income differences persist in the long run.

Weed management decision aids have proliferated in recent years, but none of them have been rigorously compared with actual farmer weed management on farm fields. This research compares the Michigan WEEDSIM/GWM bioeconomic model and the CORNHERB and SOYHERB herbicide selection models with farmer weed management in Michigan. In 19 site-years of research in corn and soybean during 1996 to 1997, we found that crop yield, weed control costs, and gross margin over weed control costs (profitability) with the computerized decision aids were not statistically superior to the farmer treatments, even at a one-sided threshold of P = 0.10. In corn the gross margin of the farmer treatment ranked highest in both years. In soybean the gross margin of the SOYHERB treatment ranked highest in 1996 and that of the WEEDSIM/GWM treatment was highest in 1997. Overall, the farmer treatment had the highest gross margin 5½ times, the CORNHERB–SOYHERB treatment 6 times, and the WEEDSIM/GWM treatment 7½ times (where ties were divided equally to give 1/2 to each). However, none of these rank differences corresponded to a statistically significant gross margin gain over the farmer treatment.