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on Network Economics |
| By: | Andre Groeger; Yanos Zylberberg |
| Abstract: | This paper studies how social networks (might fail to) shape agricultural practices. We exploit (i) a unique census of agricultural production nested within delineated land parcels and (ii) comprehensive social network data within four repopulated villages of rural Vietnam. In a first step, we extract exogenous variation in network formation from home locations within the few streets that compose each village (populated through staggered population resettlement), and we estimate the return to social links in the adoption of highly-productive crops. We find a large network multiplier, in apparent contradiction with lowadoption rates. In a second step, we study the structure of network formation to explain this puzzle: social networks display large homophily, and valuable links between heterogeneous households are rare. Due to the clustered nature of networks and the dynamic, endogenous propagation of agricultural practices, there are decreasing returns to social links, and policies targeting “inbetweeners” are most able to mitigate this issue. |
| Keywords: | technology adoption, social networks |
| JEL: | D85 O13 |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:bge:wpaper:1426&r=net |
| By: | Busch, Christian; Barkema, Harry |
| Abstract: | Previous research has shown that networks are vital for scaling the impact of social enterprises. However, at present, insight into how and why social enterprises successfully orchestrate networks over time as they scale, particularly in the Sub-Saharan African emerging economy context, is scant. Theoretically sensitized by social network theory, our inductive study of six Kenyan social enterprises analyzed their phase-contingent network orchestration. Our findings show how and why entrepreneurial contextual bridging and circumventing social liability are important for initial scaling, whereas aligned capacity building as well as aligning incentives with political actors become necessary to develop and navigate social business ecosystems. In sum, we contribute a deeper understanding of how and why agentic network actions help social entrepreneurs achieve success as they scale in an emerging economy context. |
| Keywords: | Business ecosystem; Comparative case study; Emerging economy; Kenya; Low-income context; Scaling; Social embeddedness; Social entrepreneurship; Social impact; Social networks; AAM requested |
| JEL: | R14 J01 L81 |
| Date: | 2022–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:115350&r=net |
| By: | Mosleh, Mohsen; Eckles, Dean (MIT); Rand, David Gertler |
| Abstract: | Empirical social networks are characterized by a high degree of triadic closure (i.e. transitivity, clustering), whereby network neighbors of the same individual are also likely to be directly connected. It is unknown to what degree this results from dispositions to form such relationships (i.e. to close open triangles) per se or whether it reflects other processes, such as homophily and more opportunities for exposure. These are difficult to disentangle in many settings, but in social media not only can they be decomposed, but platforms frequently make decisions that can depend on these distinct processes. Here, using a field experiment on social media, we randomize the existing network structure that a user faces when followed by a target account that we control, and we examine whether they reciprocate this tie formation. Being randomly assigned to have an existing tie to an account that follows the target user increases tie formation by 35%. Through the use of multiple control conditions in which the relevant tie is absent (never existent or removed), we are able to attribute this effect specifically to a small variation in the stimulus that indicates the presence (or absence) of a potential mutual follower. Theory suggests that triadic closure should be especially likely in open triads of strong ties, and we find evidence of larger effects when the subject has interacted more with the existing follower. These results indicate a substantial role for dispositions toward triadic closure, which platforms and others can choose to leverage in encouraging tie formation, with implications for network structure and the diffusion of information in online networks. |
| Date: | 2024–01–24 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:ys8zw&r=net |
| By: | Thibault Rolland (ARAMIS - Algorithms, models and methods for images and signals of the human brain = Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain [ICM Paris] - Inria de Paris - Inria - Institut National de Recherche en Informatique et en Automatique - ICM - Institut du Cerveau = Paris Brain Institute - AP-HP - Assistance publique - Hôpitaux de Paris (AP-HP) - INSERM - Institut National de la Santé et de la Recherche Médicale - CHU Pitié-Salpêtrière [AP-HP] - AP-HP - Assistance publique - Hôpitaux de Paris (AP-HP) - SU - Sorbonne Université - SU - Sorbonne Université - CNRS - Centre National de la Recherche Scientifique); Fabrizio De Vico Fallani (ARAMIS - Algorithms, models and methods for images and signals of the human brain = Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain [ICM Paris] - Inria de Paris - Inria - Institut National de Recherche en Informatique et en Automatique - ICM - Institut du Cerveau = Paris Brain Institute - AP-HP - Assistance publique - Hôpitaux de Paris (AP-HP) - INSERM - Institut National de la Santé et de la Recherche Médicale - CHU Pitié-Salpêtrière [AP-HP] - AP-HP - Assistance publique - Hôpitaux de Paris (AP-HP) - SU - Sorbonne Université - SU - Sorbonne Université - CNRS - Centre National de la Recherche Scientifique, ICM - Institut du Cerveau = Paris Brain Institute - AP-HP - Assistance publique - Hôpitaux de Paris (AP-HP) - INSERM - Institut National de la Santé et de la Recherche Médicale - CHU Pitié-Salpêtrière [AP-HP] - AP-HP - Assistance publique - Hôpitaux de Paris (AP-HP) - SU - Sorbonne Université - SU - Sorbonne Université - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | In many fields of science and technology we are confronted with complex networks. Making sense of these networks often require the ability to visualize and explore their intermingled structure consisting of nodes and links. To facilitate the identification of significant connectivity patterns, many methods have been developed based on the rearrangement of the nodes so as to avoid link criss-cross. However, real networks are often embedded in a geometrical space and the nodes code for an intrinsic physical feature of the system that one might want to preserve. For these spatial networks, it is therefore crucial to find alternative strategies operating on the links and not on the nodes. Here, we introduce Vizaj a javascript web application to render spatial networks based on optimized geometrical criteria that reshape the link profiles. While optimized for 3D networks, Vizaj can also be used for 2D networks and offers the possibility to interactively customize the visualization via several controlling parameters, including network filtering and the effect of internode distance on the link trajectories. Vizaj is further equipped with additional options allowing to improve the final aesthetics, such as the color/size of both nodes and links, zooming/rotating/translating, and superimposing external objects. Vizaj is an open-source software which can be freely downloaded and updated via a github repository. Here, we provide a detailed description of its main features and algorithms together with a guide on how to use it. Finally, we validate its potential on several synthetic and real spatial networks from infrastructural to biological systems. We hope that Vizaj will help scientists and practitioners to make sense of complex networks and provide aesthetic while informative visualizations. |
| Keywords: | Complex systems, Physical networks, Dataviz, Software, Art |
| Date: | 2023–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03837671&r=net |