Models as Social Actors in the Diffusion of AI Innovations: A Multilayer, Heterogeneous, Dynamic Network Perspective

Artificial Intelligence (AI) has emerged as a crucial facet of contemporary technological innovation, influencing diverse domains. Consequently, understanding the diffusion and evolution of AI innovations is vital. Scholarly publications have commonly served as proxies for studying these AI innovations. However, previous studies on publication diffusion have largely overlooked the role of models, which is particularly integral for AI innovations as they bridge upstream datasets and downstream applications. Moreover, models form an interdependent network due to their combinational evolution. This paper addresses this gap, examining how the location, movement, and speed of model movement in that model network affect the dissemination of AI research. Using a four-layer network—author collaborations, paper citations, model dependencies, and keyword co-occurrences—we examine 345,383 AI papers from 2000 to 2022. This research aims to contribute to the diffusion of innovation literature and dynamic network analysis, offering several novel insights and advancements

Diffusion of Competing Innovations: The Effects of Network Structure on the Provision of Healthcare

Medical innovations, in the form of new medication or other clinical practices, evolve and spread through health care systems, impacting on the quality and standards of health care provision, which is demonstrably heterogeneous by geography. Our aim is to investigate the potential for the diffusion of innovation to influence health inequality and overall levels of recommended care. We extend existing diffusion of innovation models to produce agent-based simulations that mimic population-wide adoption of new practices by doctors within a network of influence. Using a computational model of network construction in lieu of empirical data about a network, we simulate the diffusion of competing innovations as they enter and proliferate through a state system comprising 24 geo-political regions, 216 facilities and over 77,000 individuals. Results show that stronger clustering within hospitals or geo-political regions is associated with slower adoption amongst smaller and rural facilities. Results of repeated simulation show how the nature of uptake and competition can contribute to low average levels of recommended care within a system that relies on diffusive adoption. We conclude that an increased disparity in adoption rates is associated with high levels of clustering in the network, and the social phenomena of competitive diffusion of innovation potentially contributes to low levels of recommended care.Innovation Diffusion, Scale-Free Networks, Health Policy, Agent-Based Modelling

How change agents and social capital influence the adoption of innovations among small farmers: Evidence from social networks in rural Bolivia

"This paper presents results from a study that identified patterns of social interaction among small farmers in three agricultural subsectors in Bolivia—fish culture, peanut production, and quinoa production—and analyzed how social interaction influences farmers' behavior toward the adoption of pro-poor innovations. Twelve microregions were identified, four in each subsector, setting the terrain for an analysis of parts of social networks that deal with the diffusion of specific sets of innovations. Three hundred sixty farmers involved in theses networks as well as 60 change agents and other actors promoting directly or indirectly the diffusion of innovations were interviewed about the interactions they maintain with other agents in the network and the sociodemographic characteristics that influence their adoption behavior. The information derived from this data collection was used to test a wide range of hypotheses on the impact that the embeddedness of farmers in social networks has on the intensity with which they adopt innovations. Evidence provided by the study suggests that persuasion, social influence, and competition are significant influences in the decisions of farmers in poor rural regions in Bolivia to adopt innovations. The results of this study are meant to attract the attention of policymakers and practitioners who are interested in the design and implementation of projects and programs fostering agricultural innovation and who may want to take into account the effects of social interaction and social capital. Meanwhile, scholars of the diffusion of innovations may find evidence to further embrace the complexity and interdependence of social interactions in their models and approaches." from Author's AbstractSocial networks, Agricultural innovation, Change agent, Social capital,

The Diffusion of Modern technologies in Namibia

Keywords: Namibia, Regional Development, Innovation Systems, Planning During the last decade, globalisation and modern technologies have engendered as much challenges as opportunities for economies of many states in several respects. This is especially true for less developed countries such as Namibia. With the rapid introduction of new modern technologies and speedy disposal of the old ones; many nation states face a spatial change. Hypothetically, they respond differently to this challenge. Innovation diffusion implies the questions: by what criteria and for whom? Moreover, diffusion suggests a process of making new technologies adopted or made available over a wide geographically defined area. If indeed, there is a diffusion of innovations in Namibia, how is it taking place? In the age of globalisation, is it global forces that are ‘shipping’ new technologies to Namibia? Could it be that innovations are closely tied to the education system and the country’s multicultural set-up? Or, is it people/companies on the move who carry innovations with? And, what is unique about Namibia, regarding this process? This paper is an attempt to discuss the processes of technology and innovation adoptions in the sectors of agriculture, fisheries and mining in Namibia – in the context of regional and local development. The main research questions focus on: Which factors promotes innovations and which ones impedes innovations, and how does local conditions change, accordingly developing an economy from a resource-based to an information society? This work seeks to develop a theory that considers regional and local development as an output of interacting local actors - a kind of ‘Reflective causation’ of development. According to this approach, the spatiality of innovation adoption and the process of transformation are primarily induced by a network of internal forces motivated by history. In this context, history not from a nationalist perspective but from a spatial viewpoint, forms the basis of a nation’s identity and models a country’s economic development. In addition to an earlier hypothesis, other factors: market strategy, demand conditions, structural elements and global forces do not halt development, they broaden and amplify the spatiality of development. The data, which forms the basis of my analysis, will be drawn from key informant interviews from June to September 2002 in the Republic of Namibia.

Consume, Modify, Share (CMS): The Interplay between Individual Decisions and Structural Network Properties in the Diffusion of Information

Widely used information diffusion models such as Independent Cascade Model, Susceptible Infected Recovered (SIR) and others fail to acknowledge that information is constantly subject to modification. Some aspects of information diffusion are best explained by network structural characteristics while in some cases strong influence comes from individual decisions. We introduce reinvention, the ability to modify information, as an individual level decision that affects the diffusion process as a whole. Based on a combination of constructs from the Diffusion of Innovations and the Critical Mass Theories, the present study advances the CMS (consume, modify, share) model which accounts for the interplay between network structure and human behavior and interactions. The model's building blocks include processes leading up to and following the formation of a critical mass of information adopters and disseminators. We examine the formation of an inflection point, information reach, sustainability of the diffusion process and collective value creation. The CMS model is tested on two directed networks and one undirected network, assuming weak or strong ties and applying constant and relative modification schemes. While all three networks are designed for disseminating new knowledge they differ in structural properties. Our findings suggest that modification enhances the diffusion of information in networks that support undirected connections and carries the biggest effect when information is shared via weak ties. Rogers' diffusion model and traditional information contagion models are fine tuned. Our results show that modifications not only contribute to a sustainable diffusion process, but also aid information in reaching remote areas of the network. The results point to the importance of cultivating weak ties, allowing reciprocal interaction among nodes and supporting the modification of information in promoting diffusion processes. These results have theoretical and practical implications for designing networks aimed at accelerating the creation and diffusion of information

Theoretical framework and methods for the analysis of the adoption-diffusion of innovations in agriculture: a bibliometric review

The adoption and diffusion of innovations are essential for both the development of production processes and the improvement of agricultural environmental sustainability, at any stage of the value chain. In recent years, social scientists have studied the diffusion and adoption of agricultural innovations from different approaches, such as innovation diffusion theory, behavioral models, econometric models, social capital and social network analysis, among others. In this study we analyze the scientific literature through a bibliometric analysis based on co-citation networks, to explore the theoretical pillars and bibliographic coupling, with which we explore the current methodological research trends of the last 50 years. The conclusions drawn from this analysis are that in recent years agricultural researchers on adoption and diffusion have designed multivariate methods that combine diverse study approaches. This review contributes to a better understanding of theory and practice in the study of the adoption and diffusion of agricultural innovations

Collaboration in scientific digital ecosystems: A socio-technical network analysis

This dissertation seeks to understand the formation, operation, organizational (collaboration) and the effect of scientific digital ecosystems that connect several online community networks in a single platform. The formation, mechanism and processes of online networks that influence members output is limited and contradictory. The dissertation is comprised of three papers that are guided by the following research questions: How does online community member’s productivity (or success) depend upon their ‘position’ in the digital networks? What are the network formation mechanism, structures and characteristics of an online community? How do scientific innovations traverse (diffuse) amongst users in online communities? A combination of exploratory, inductive and deductive research designs is applied sequentially but in a non-linear manner to address research question. The dissertation contributes to the literature on scientific collaboration, digital communities of creation, social network modelling and diffusion of innovation. The first paper applies network theory and spatial probit autocorrelative modelling technique to evaluate how member developer’s positioning in digital community correlate with his/her productivity. The second paper looks at the dynamics of developer’s participation in online developers’ network for a period spanning 7-years using exponential random graph models (ERGM). This paper applies theory of network (network science) to model network formation patterns in developer community. The third paper, like the first, applies network theory and to understand user network characteristics and communication channels which influence diffusion of scientific innovations. Bass and spatial probit autocorrelative models are applied for this analysis. Data from this study was mined from developers, authors and user communities of nanoHUB.org cyberinfrastructure platform. NanoHUB.org is a science and engineering online ecosystem comprising self-organized researchers, educators, and professional communities in eight member institutions that collaborate, share resources and solve nanotechnology related problems including development and usage of tools (scientific innovation). Data from collaboration and information sharing activities was used to create the developers, authors and user networks that were used for analysis. Results of the first paper show that the spatial autocorrelation parameter of the spatial probit model is negative and statistically different from zero. The negative spatial spillover effect in the developer network imply that developers that are embedded in the network have a lower probability of getting more output. The structural network characteristics of eigen vector centrality had statistically significant effects on probability of being more productive. Developers who are also authors were found to be more productive than those in one network. The implications of these findings is that developers will benefit from being in multiple network spaces and by associating with more accomplished developers. The autocorrelative and interaction models also reveal various new modelling approach of accounting for network autocorrelation effects to online member. Results of the second paper show that developers form in a manner that follow a pure uniform random distribution. Results also show that developer’s collaborative mechanisms are characterized by low tendencies to reciprocate and form homophiles (tendency of developers to associate with similar peers) but high tendency to form clusters. The implications of network formation mechanism and processes are that developers are forming in a purely random and self-organized manner and minimum efforts should be applied in trying to organize and influence the community organization. The results also reveal that a simple link to link ERGM and stochastic dominance criteria can be combined to characterize the network formation characteristics just like the ERG(p*) model but have an advantage of overcoming degeneracy challenges associated with ERG(p*) models. Results of the third paper show that bass model is a good predictor for diffusion of scientific innovations (tools) in online community setting. Results also show different innovations have varying levels and rates of adoption and these were influenced by both external and internal factors. Results of the micro-based model found degrees and betweeness centrality as some of the internal variables that have positive influence on the adoption of innovation while centrality measures of power or leadership were found to have negative influence of adoption process. The relative time taken to run a simulation (measured as job usage time) was also found to be negatively influencing diffusion. The implication of the study results is that bass model is a good fit for evaluating and forecasting adoption of innovation in online communities. Moreover, network structural characteristics are responsible for adoption of innovation adoption and policy making should consider tool adoption enhancing ones. Additionally, researchers could further explore the network structural characteristics that are driving diffusion of innovation

Business models for climate services: An analysis

Climate services support mitigation and adaptation to climate change and encourage a science-based and climate-informed policy development. A performing market is vital for supporting uptake of climate services. The diffusion of innovations depends on how business models – meant as firms’ strategic choices to create, capture and share value within a value network – are employed. Innovation in business model, rather than product innovation only, has been proved useful for overcoming bottlenecks associated with development and diffusion of technologies. But only few studies have analysed how business models are used within the context of climate services. We fill this gap by using a sample of 32 climate services provisions at different stage of development. We use an original and revised version the Business Model Canvas as a framework to facilitate the data collection and analysis processes. A quali-quantitative approach is employed to tackle the content of the administered semi-structured interviews and to map them into a connected set of nodes representing concepts as provided by the selected informants. By combining Content and Network Analysis we present how business model aspects interact both within and across components. We find that the Value Network in which climate services operate is crucial for success, while a subscription, online-based infrastructure is a widespread tool in reaching the target users. The creation of partnerships and consortia of organisations allows mutual learning opportunities to happen and boosts the innovation behind these products. We focus on the graph giant component to highlight the role of co-creation approach in generating direct and indirect incremental innovations while delivering seasonal forecasts and tailor-made services. Finally, we call for tighter link between business and climate-related aspects to enhance the importance of financial considerations around climate services provision

Critical factors for implementing and diffusing sustainable Product-Service Systems: Insights from innovation studies and companies' experiences

This is the post-print version of the final paper published in Journal for Cleaner Production. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2012 Elsevier B.V.Eco-efficient Product-Service System (PSS) innovations represent a promising approach to sustainability. However the adoption of such business strategies is still very limited because it often involves significant corporate, cultural and regulatory barriers. An important challenge is not only to conceive eco-efficient PSS concepts, but also to understand the contextual conditions that facilitate their societal embedding, and which strategies and development pathways are the most appropriate. The combination of theoretical insights from innovation studies (in particular Strategic Niche Management and Transition Management) and a case studies research (exploring the innovation journeys made by six companies in introducing their eco-efficient PSS innovations in the market) is used to investigate the factors that influence the implementation and diffusion of this kind of innovations. The article provides a structured overview of these factors, grouping them in four clusters: implementation of socio-technical experiments; establishment of a broad network of actors; building up of a shared project vision; creation of room for broad and reflexive learning processes. Based on these results it is argued that a broader and more strategic system approach should be adopted by companies. Companies should focus not only on the PSS solution and its value chain, but also on the contextual conditions that may favour or hinder the societal embedding of the PSS itself. The article concludes by outlining a key area for future research