The research team, led by Koorosh Azizi of Tennessee State University and The University of Texas at Austin, together with Margaret Garcia of Arizona State University, Dev Niyogi and R. Patrick Bixler of The University of Texas at Austin, set out to explain why policy support for green stormwater infrastructure has not translated into the collective impact that planners hoped for. Individual household decisions matter, but the hydrological benefits of decentralized stormwater control only materialize at scale, when large fractions of a watershed’s impervious surface are treated. That means the crucial question for cities is not whether a few enthusiastic early adopters will install a rain garden, but whether adoption will diffuse through neighborhoods in a self-sustaining wave.

To answer it, the team constructed one of the most empirically grounded simulations of green infrastructure uptake to date. The model represents individual households as agents, each endowed with socio-demographic attributes drawn from census data, parcel attributes from municipal GIS records, and behavioral traits calibrated against a de-identified household survey. The agents form social networks, exchange influence through peer effects, and update internal psychological states, including awareness of green stormwater practices, personal norms, attitudes toward adoption, and social capital, the web of trust and reciprocity that shapes how neighbors persuade one another. Adoption occurs when a household’s intention crosses an individual threshold, a formulation rooted in established behavioral theory, including the theory of planned behavior and social-cognitive frameworks of observational learning.

What makes the model technically distinctive is its layered experimental design. The researchers staged mechanisms incrementally, from a static baseline in which nothing changes, through layers that separately activate feasibility and affordability constraints, social capital dynamics, and behavioral channels for awareness, norms and attitudes, up to a fully coupled configuration in which gains in one psychological variable carry over into others within each simulation step. Each layer thereby isolates a candidate engine of diffusion, and the city of Austin, divided into its ten council districts, serves as the empirical laboratory. Over 120 simulated time steps, the model tracks how many households adopt two broad classes of practices: structural installations such as rain gardens and permeable surfaces, and lower-cost rain-catching measures such as barrels and cisterns.

The central finding is stark: no single factor is sufficient to trigger widespread adoption. Visibility alone, in the form of neighbors’ visible installations, generates curiosity but not commitment if residents cannot afford or physically manage the conversion. Capacity alone, even when subsidies make practices affordable, produces only scattered adoption if households never see the practice working next door or receive no social encouragement. And social capital without concrete, visible examples and feasible options can reinforce skepticism as easily as enthusiasm. Sustained diffusion emerges only when the three mechanisms operate together, creating a feedback loop in which visible adoption builds social proof, social proof lowers the perceived risk of conversion, and capacity converts intention into installed infrastructure that becomes visible in turn.

Because neighborhoods differ in their endowments of these three ingredients, their adoption trajectories diverge into qualitatively distinct patterns. Some districts exhibit rapid takeoff, with adoption accelerating once a critical mass of installations and social connections is reached. Others show delayed diffusion, where early progress is slow but momentum eventually builds as awareness and networks mature. Still others display episodic growth, alternating bursts of uptake with plateaus, or persistent stagnation, in which adoption never escapes its initial low level. The citywide average, the authors show, masks this heterogeneity almost completely, meaning that aggregate statistics can conceal neighborhoods that need entirely different interventions.

The model also reveals that the dominant psychological mechanism driving adoption shifts over time and across space. In some districts, adoption is sustained chiefly by growing awareness; in others, personal norms, attitudes or social capital take turns leading, sometimes within the same neighborhood as the diffusion process matures. This shifting dominance has practical consequences: a one-size-fits-all campaign that emphasizes environmental messaging may work in one district while doing little in another where the binding constraint is affordability or the absence of visible examples. Diagnostic tools like this model, the authors argue, can help cities identify neighborhood-specific barriers and target resources accordingly, whether through demonstration projects, cost-sharing programs, or community-network building.

The theoretical contribution is equally significant. Diffusion-of-innovations research has long recognized the roles of observability, compatibility and social networks, and studies of rooftop solar adoption have documented peer effects that cluster installations spatially. But green stormwater infrastructure poses a harder test, because it is what the authors characterize as a complex contagion: a behavior whose benefits are collective, whose adoption requires repeated social reinforcement, and whose costs fall on private parcels. By embedding behavioral dynamics, physical feasibility and social network structure in a single spatially explicit framework, the study provides a generative explanation of how those ingredients combine, and it connects the stormwater literature to broader debates about infrastructure inequality and the legacy effects of segregation on urban green space.

The implications for practice are direct. Cities seeking to accelerate green stormwater infrastructure, whether to reduce pluvial flooding, cut pollutant loads, or meet regulatory requirements, should stop asking which single lever works best and start asking whether the three conditions are jointly present. Where visibility is low, demonstration installations and open-garden events can seed social proof. Where capacity is the constraint, reverse auctions, rebates and streamlined permitting can lower the feasibility barrier, an approach consistent with earlier household incentive studies. Where social capital is thin, partnerships with community organizations may be needed to build the trust through which peer influence travels. The Austin model, whose data and code are openly available through Zenodo and GitHub, offers planners a template for testing these strategies in silico before deploying them in the watershed, a step the authors suggest could meaningfully shorten the long wait for green infrastructure to deliver its promised resilience at city scale.

Subject of Research: Agent-based modeling of the social and structural drivers of household adoption of green stormwater infrastructure in cities

Article Title: Sustaining green stormwater infrastructure adoption in cities

Article References: Sustaining green stormwater infrastructure adoption in cities. (n.d.). https://doi.org/10.1038/s44284-026-00520-1

Image Credits: AI Generated

DOI: 10.1038/s44284-026-00520-1

Keywords: green stormwater infrastructure, agent-based model, urban resilience, rain gardens, social capital, diffusion of innovations, Austin Texas, nature-based solutions, urban flooding, household adoption, stormwater management, neighborhood inequality

The research team, led by Edward Afum Banahene and Enoch Kwame Tham-Agyekum of the Kwame Nkrumah University of Science and Technology, with collaborators at the University of Pretoria, Mwalimu Julius K. Nyerere University of Agriculture and Technology, the University of Cape Coast, and the Malawi University of Science and Technology, set out to answer a deceptively simple question: which communication channels actually move farmers from awareness to action? Climate variability in Ghana—erratic rainfall, prolonged dry spells, and progressive soil degradation—continues to undermine agricultural productivity and food security. Climate-resilient agricultural practices, ranging from drought-tolerant and early-maturing crop varieties to intercropping, conservation tillage, agroforestry, organic manure application, rainwater harvesting, cover cropping, and the use of weather forecasts, have been promoted for years. Yet adoption remains low and inconsistent, despite growing policy support.

The researchers argue that the bottleneck is not the existence of technologies but the communication mechanisms that carry knowledge of them. Farmers must be aware of a practice, understand how it works, and trust the source before they will implement it. Drawing on Diffusion of Innovations theory and the framework of Agricultural Knowledge and Information Systems, the team compared multiple pathways within a single analytical framework: face-to-face extension, community radio, digital platforms and social media, mobile-based services, cooperatives and farmer organizations, peer learning networks, farmer field schools, demonstration plots, agricultural shows, participatory video, community theater, and village knowledge-sharing platforms. Crucially, they combined farmers’ perceptions of trust, accessibility, credibility, and convenience with measurable behavioral outcomes, and used multivariate statistics to control for socio-economic factors such as education, gender, farm size, income, and extension contact.

Methodologically, the study employed a descriptive, quantitative design. From a population of roughly 40,000 smallholder farmers in the municipality, a sample of 396 was drawn using Yamane’s formula at a 95 percent confidence level and a 5 percent margin of error. Two-stage sampling first purposively identified communities cultivating climate-sensitive crops, then randomly selected farmers from lists supplied by the Ministry of Agriculture and farmer-based organizations. Structured questionnaires with Likert-scale items were administered face-to-face in December 2025, with reliability confirmed by Cronbach’s alpha values between 0.78 and 0.81 across the constructs of accessibility, relevance, effectiveness, and trust. Ethical clearance was granted by KNUST’s Humanities and Social Sciences Research Ethics Committee, and participation was voluntary and anonymized.

The results paint a vivid picture of a communication landscape in which social embeddedness trumps broadcast reach. Cooperatives and farmer organizations emerged as the most frequently used pathway, with a mean usage score of 3.92 on a five-point scale, followed closely by community radio (3.77), digital platforms and social media (3.73), peer learning networks (3.73), and farmer-to-farmer communication (3.60). But frequency of use is not the same as influence. Spearman rank correlation analysis revealed that peer learning networks and farmer-to-farmer communication exhibited the strongest positive and statistically significant associations with nearly every climate-resilient practice measured. Peer learning networks correlated at 0.756 with intercropping, 0.714 with conservation tillage, 0.523 with organic manure application, and 0.479 with the use of climate information. Farmer-to-farmer communication showed similarly strong associations with intercropping (0.630), conservation tillage (0.606), mulching (0.565), and cover cropping (0.440).

These correlations, the authors argue, reflect the mechanics of social learning. Peer exchange allows direct observation of outcomes, experimentation, and feedback, reducing the uncertainty that surrounds new practices. Trust, shared norms, and cumulative experience shape decision-making in ways that one-way broadcasts cannot. Climate-resilient farming, in this view, is not a solitary undertaking but a collective one, embedded in social systems. Extension strategies that institutionalize peer-based learning—lead farmers, farmer champions, group-based experimentation—are therefore more likely to achieve sustainable and scalable resilience than top-down information delivery.

The study’s regression analysis added a socio-economic dimension. Farmer group membership significantly predicted the use of agricultural shows and exhibitions (β = 0.315, p < 0.05), community theater (β = 0.338, p < 0.05), and participatory video (β = 0.423, p < 0.05), suggesting that organized groups act as gateways to collective, experiential communication formats. Engagement in off-farm income activities significantly predicted farmer-to-farmer communication (β = 0.309, p < 0.05), indicating that time-constrained farmers gravitate toward fast, trusted peer exchanges rather than formal training sessions. Intriguingly, education, age, gender, farm size, and income were largely insignificant predictors of pathway use, hinting that in this setting, social dynamics matter more than individual human capital. A possible substitution effect also surfaced: farmers with frequent extension contact showed marginally lower use of community radio and digital media, suggesting imperfect integration between formal and informal information systems.

Not every finding flattered conventional wisdom. Farmer field schools and demonstration plots—long staples of agricultural extension—displayed significant negative correlations with adoption, including −0.327 for intercropping and −0.297 for conservation tillage. The authors attribute this to poor contextualization, infrequent delivery, didactic teaching styles, and time lags before benefits materialize. NGO and donor-funded groups showed weak negative effects, and climate adaptation networks were largely ineffective, likely lacking visibility, structure, and sustained engagement. Community radio, digital and social media, and participatory video showed low or insignificant correlations with actual adoption, reinforcing the argument that while mass media excels at awareness creation, it lacks the interactivity and specificity required for behavioral change. Mobile-based services occupied a middle ground, with moderate but consistent positive correlations, particularly with drought-tolerant varieties (0.161) and climate information use (0.212), positioning them as valuable tools for the knowledge and early decision stages of adoption.

Perception data reinforced the hierarchy of trust. Extension officers were the most trusted information actors (mean 4.25), followed by farmer networks and cooperatives (3.84), while trust in mobile applications (3.02) and social media (3.22) remained moderate—evidence that exposure does not automatically breed confidence. Farmers rated information clarity highly (4.05) and peer-to-peer interaction as especially effective for knowledge transfer (4.07), but field demonstrations (2.01) and climate adaptation networks (1.96) scored lowest, pointing to weak institutional embedding rather than intrinsic ineffectiveness. The study also identified barriers to adoption using Kendall’s coefficient of concordance, which confirmed significant consensus among respondents. Risk aversion and fear of yield loss ranked as the most critical constraint (mean rank 3.66), followed by lack of access to accurate and timely climate information, low education and technical knowledge, labor and financial constraints, distrust in information sources, and land tenure insecurity. Notably, language barriers ranked least significant, suggesting that most information in Techiman is already delivered in familiar local dialects.

The implications extend well beyond Ghana. The authors recommend scaling peer learning platforms, integrating timely and localized climate information into channels farmers already trust, developing visual, stepwise communication materials, providing financial and labor support mechanisms such as collective labor schemes and staggered input repayment, and delivering advice through credible local actors including opinion leaders and farmer representatives. They caution that the cross-sectional design limits causal inference and that self-reported data may carry recall and social desirability bias. Still, the central message is clear and potentially transformative for adaptation policy across Africa: psychological and informational barriers outweigh structural ones, and the most powerful communication technology in climate-smart agriculture may not be a smartphone or a radio transmitter at all, but the trusted voice of a fellow farmer standing at the edge of a demonstration field, describing what actually worked.

Subject of Research: The relationship between communication pathways and smallholder farmers' adoption of climate-resilient agricultural practices in Techiman Municipality, Ghana.

Article Title: Talking climate, growing change: communication pathways and farmer adoption of resilient practices in Techiman, Ghana

Article References: Talking climate, growing change: communication pathways and farmer adoption of resilient practices in Techiman, Ghana. (n.d.). https://doi.org/10.1007/s13412-026-01136-6

Image Credits: AI Generated

DOI: 10.1007/s13412-026-01136-6

Keywords: climate-resilient agriculture, communication pathways, smallholder farmers, peer learning, Ghana, adoption, agricultural extension, climate information, farmer organizations, diffusion of innovations, Techiman, risk aversion

The study, published in the journal Discover Informatics, examined eight Ghanaian universities with operational institutional repositories, including the University of Ghana, Kwame Nkrumah University of Science and Technology, the University of Cape Coast, the University of Education Winneba, the University for Development Studies, Ashesi University, the Ghana Institute of Journalism, and the University of Professional Studies Accra. Led by De-Graft Johnson Dei and Karim Awudu, the research team surveyed 120 respondents drawn from ICT personnel, repository managers, academic librarians, systems librarians, and faculty members, then followed up with in-depth interviews with twelve senior experts. The design was a sequential explanatory mixed-methods approach, meaning the survey results shaped the questions asked in later interviews, and the two strands of evidence were triangulated during interpretation.

The headline finding is sobering. Forty percent of respondents said their institutions had no digital rights management mechanism in place at all. Access control was the most commonly implemented practice, appearing at 44.2 percent of institutions, while advanced techniques such as digital watermarking and encryption were implemented at only 9.2 percent. Usage tracking, copyright auditing, and automated licensing enforcement were similarly rare. Interview participants described repositories that upload content without defined rights policies, verify permissions manually, and have no idea who downloads what or where it ends up. One participant at the University for Development Studies put it bluntly: access matters more than protection. Another observed that if content is on the internet, people assume it is free to use, a presumption that puts author rights at risk.

Against this backdrop, blockchain technology has been proposed as a transformative tool. A blockchain is a distributed ledger in which transactions are recorded in cryptographically verified, time-stamped blocks linked to their predecessors, maintained across a network of nodes rather than a single central authority. Because no single party controls the record, entries cannot be quietly altered, and every change leaves a permanent, auditable trail. For digital rights management, this architecture offers several distinct functions: authorship verification through immutable timestamps and digital signatures, provenance tracking across the scholarly lifecycle, content integrity through cryptographic verification, and automated rights enforcement through smart contracts, which are self-executing programs that apply licensing terms without continuous administrative intervention.

The researchers grounded their analysis in two complementary theoretical lenses. The Technology-Organization-Environment framework, developed by Tornatzky and Fleischer, examines how technological features, organizational capacity, and environmental conditions such as national policy shape whether institutions adopt an innovation. Diffusion of Innovations theory, articulated by Everett Rogers, explains how individual stakeholders perceive new ideas through the attributes of relative advantage, compatibility, complexity, trialability, and observability. Together, the frameworks allowed the team to assess both the structural readiness of Ghanaian universities and the attitudes of the people who would actually operate blockchain-enabled systems.

Awareness of blockchain turned out to be uneven. Overall, 62.5 percent of respondents had heard of the technology, but mean perceived understanding was low at 2.31 on a five-point scale. ICT personnel were far ahead, with 86.7 percent awareness and a mean understanding score of 3.82, while faculty members lagged at 33.3 percent awareness and a mean of 1.74. Interviews revealed persistent conceptual confusion, with some participants equating blockchain entirely with Bitcoin and others describing it as futuristic but unproven in a library context. Several respondents expressed a genuine appetite for training, noting that interest exists but workshops and webinars do not. According to Diffusion of Innovations theory, these conditions mark an early adoption stage characterized by low observability and high perceived complexity, yet also a latent receptiveness that targeted demonstration could convert into adoption.

Institutional readiness fared worse. The overall preparedness score was 2.25, rated as poor, and only 18.3 percent of respondents believed their infrastructure could support blockchain. A striking 81.7 percent said their digital library strategies made no mention of the technology. Funding was the dominant constraint, cited by 74.2 percent, followed by technical complexity at 74.2 percent, shortage of qualified staff at 72.5 percent, and absence of legal and regulatory frameworks at 68.3 percent. Participants described server capacity too limited to host current systems, ICT plans with no blockchain reference whatsoever, and donor projects that fund basic digital libraries but not cutting-edge infrastructure. In northern Ghana, unreliable internet and electricity compounded the problem, cited by 54.2 percent of respondents.

Yet the appetite for blockchain’s benefits was remarkably strong. Tamper-proof authorship verification topped the list, endorsed by 78.3 percent of respondents with a mean rating of 4.21, followed by improved content authenticity and integrity at 74.2 percent and transparent audit trails at 71.7 percent. Smart contract automation of copyright enforcement drew support from 66.7 percent, blockchain timestamping from 61.7 percent, and decentralized data control from 63.3 percent. Librarians interviewed for the study described repeated incidents of downloaded content being renamed and shared without credit, and saw in blockchain a way to safeguard the uniqueness of their researchers’ work. Others noted that precise access tracking could transform impact monitoring, and that smart contracts could enforce Creative Commons licenses without manual policing.

On strategy, stakeholders favored cautious, low-risk pathways. Staff training and capacity building was the most endorsed approach at 79.2 percent, followed by pilot blockchain repository modules at 76.7 percent and phased implementation at 74.2 percent. Open-source platforms such as Hyperledger attracted 72.5 percent support, reflecting a preference for affordable, flexible tools over commercial systems. Multidisciplinary task forces spanning librarians, attorneys, and IT professionals, donor and government funding, and regional consortia all received strong ratings, while alignment with national education policy goals ranked lowest at 60.8 percent, exposing a strategic disconnect between institutional action and frameworks set by the Ministry of Education and the Ghana Tertiary Education Commission.

The study concludes that blockchain-enabled digital rights management in Ghanaian repositories is a promising but still emerging innovation, transformative in potential yet constrained by infrastructure, funding, expertise, and policy. The authors recommend phased implementation, pilot projects beginning perhaps with postgraduate theses, open-source tools, interdisciplinary collaboration, and sustained investment in digital infrastructure and human capacity. They also caution that the findings rest on self-reported perceptions from eight universities and do not evaluate operational blockchain systems, leaving room for future work on prototypes, longitudinal adoption studies, and integration with technologies such as big data analytics and large language models. For now, the message is clear: Ghana’s repositories hold valuable scholarship that is largely unprotected, and while blockchain is no silver bullet, stakeholders across the country’s universities are ready to explore whether a decentralized ledger can finally give their research the trust and security it deserves.

Subject of Research: Blockchain adoption for digital rights management in Ghanaian university institutional repositories

Article Title: Evaluating blockchain adoption for digital rights management in institutional repositories

Article References: Johnson Dei, D.-G., & Awudu, K. (2026). Evaluating blockchain adoption for digital rights management in institutional repositories. Discover Informatics, 1(1), Article 5. https://doi.org/10.1007/s44564-026-00008-z

Image Credits: AI Generated

DOI: 10.1007/s44564-026-00008-z

Keywords: blockchain technology, digital rights management, institutional repositories, Ghana, higher education, scholarly communication, smart contracts, copyright protection, digital preservation, open access, TOE framework, Diffusion of Innovations