Multilevel network interventions: Goals, actions, and outcomes

Robins, Garry; Lusher, Dean; Broccatelli, Chiara; Bright, David; Gallagher, H. Colin; Karkavandi, Maedeh Aboutalebi; Matouš, Petr; Coutinho, James; Wang, Peng; Koskinen, Johan; Roden, Bopha; Sadewo, Giovanni Radhitio Putra

doi:10.1016/j.socnet.2022.09.005

Cited by 8 publications

(4 citation statements)

References 112 publications

(147 reference statements)

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“…Building upon a long line of anthropological studies [13][14][15]18,43,45 , our work provides a baseline understanding of the broad importance of one's primary social environments, including their social networks and geographic locations, on the allocation of household assets in shaping disparities in resourceownership in a poverty-stricken setting. Findings here suggest that large-scale social intervention programs that account for the spillover potential of economic resources may be more efficient and effective than programs that ignore the importance of social connectedness in lower-income populations 31,38 . To this end, our work offers several avenues for future research.…”

Section: Discussionmentioning

confidence: 85%

“…Third, several longstanding questions in social and natural sciences relate to the puzzle of whether small-scale social processes can lead to emergent phenomena at the macro level [26][27][28][29][30] . This micro-tomacro question, pertinent in understanding phenomena such as the recent COVID-19 pandemic 31 and climate change responses 32 , seeks to clarify how local social interactions might traverse into populationlevel dynamics. However, understanding these micro-macro linkages remains a formidable challenge, often due to the difficulties of harmonising and modelling the expected social patterns and the inherent randomness in human social interactions 33 .…”

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confidence: 99%

“…Yet, the link between macro-and micro-level economic outcomes, alongside the specific types of social interactions that may strengthen returns capable of influencing economic disparities, remains poorly understood. Unpacking the varying network dynamics at play is therefore likely to contribute to a more refined understanding of how to enhance the effectiveness and efficiency of social policy interventions 31,38 .…”

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confidence: 99%

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Local Network Interaction as a Mechanism for Wealth Inequality

Yu,

Wang,

Kabudula

et al. 2024

Nat Commun

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Given limited institutional resources, low-income populations often rely on social networks to improve their socioeconomic outcomes. However, it remains in question whether small-scale social interactions could affect large-scale economic inequalities in under-resourced contexts. Here, we leverage population-level data from one of the poorest South African settings to construct a large-scale, geographically defined, inter-household social network. Using a multilevel network model, we show that having social ties in close geographic proximity is associated with stable household asset conditions, while geographically distant ties correlate to changes in asset allocation. Notably, we find that localised network interactions are associated with an increase in wealth inequality at the regional level, demonstrating how macro-level inequality may arise from micro-level social processes. Our findings highlight the importance of understanding complex social connections underpinning inter-household resource dynamics, and raise the potential of large-scale social assistance programs to reduce disparities in resource-ownership by accounting for local social constraints.

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Section: Discussionmentioning

confidence: 85%

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confidence: 99%

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confidence: 99%

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Local Network Interaction as a Mechanism for Wealth Inequality

Yu,

Wang,

Kabudula

et al. 2024

Nat Commun

Self Cite

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“…Furthermore, the two-mode network consistently surfaces as an illustrative mechanism to depict the nuanced dynamics between individuals and their aligned entities or occurrences (Snijders et al, 2013;Jacobsen et al, 2022;Robins et al, 2023). Often paralleled with affiliation networks, a term coined by Wasserman and Faust (1994), it encapsulates a bifurcated perception of knowledge, segregating it into explicit and implicit realms.…”

Section: Literature Reviewmentioning

confidence: 99%

Knowledge-driven networking and ambidextrous innovation equilibrium in power systems transition

Xing,

Chin,

Huang

et al. 2024

JKM

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Purpose The ongoing paradigm shift in the energy sector holds paramount implications for the realization of the sustainable development goals, encompassing critical domains such as resource optimization, environmental stewardship and workforce opportunities. Concurrently, this transformative trajectory within the power sector possesses a dual-edged nature; it may ameliorate certain challenges while accentuating others. In light of the burgeoning research stream on open innovation, this study aims to examine the intricate dynamics of knowledge-based industry-university-research networking, with an overarching objective to elucidate and calibrate the equilibrium of ambidextrous innovation within power systems. Design/methodology/approach The authors scrutinize the role of different innovation organizations in three innovation models: ambidextrous, exploitative and exploratory, and use a multiobjective decision analysis method-entropy weight TOPSIS. The research was conducted within the sphere of the power industry, and the authors mined data from the widely used PatSnap database. Findings Results show that the breadth of knowledge search and the strength of an organization’s direct relationships are crucial for ambidextrous innovation, with research institutions having the highest impact. In contrast, for exploitative innovation, depth of knowledge search, the number of R&D patents and the number of innovative products are paramount, with universities playing the most significant role. For exploratory innovation, the depth of knowledge search and the quality of two-mode network relations are vital, with research institutions yielding the best effect. Regional analysis reveals Beijing as the primary hub for ambidextrous and exploratory innovation organizations, while Jiangsu leads for exploitative innovation. Practical implications The study offers valuable implications to cope with the dynamic state of ambidextrous innovation performance of the entire power system. In light of the findings, the dynamic state of ambidextrous innovation performance within the power system can be adeptly managed. By emphasizing a balance between exploratory and exploitative strategies, stakeholders are better positioned to respond to evolving challenges and opportunities. Thus, the study offers pivotal guidance to ensure sustained adaptability and growth in the power sector’s innovation landscape. Originality/value The primary originality is to extend and refine the theoretical understanding of ambidextrous innovation within power systems. By integrating several theoretical frameworks, including social network theory, knowledge-based theory and resource-based theory, the authors enrich the theoretical landscape of power system ambidextrous innovation. Also, this inclusive examination of two-mode network structures, including the interplay between knowledge and cooperation networks, unveils the intricate interdependencies between these networks and the ambidextrous innovation of power systems. This approach significantly widens the theoretical parameters of innovation network research.

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Structural resilience and recovery of a criminal network after disruption: a simulation study

Diviák

2023

J Exp Criminol

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Objectives Criminal networks tend to recover after a disruption, and this recovery may trigger negative unintended consequences by strengthening network cohesion. This study uses a real-world street gang network as a basis for simulating the effect of disruption and subsequent recovery on network structure. Methods This study utilises cohesion and centrality measures to describe the network and to simulate nine network disruptions. Stationary stochastic actor-oriented models are used to identify relational mechanisms in this network and subsequently to simulate network recovery in five scenarios. Results Removing the most central and the highest-ranking actors have the largest immediate impact on the network. In the long-term recovery simulation, networks become more compact (substantially so when increasing triadic closure), while the structure disintegrates when preferential attachment decreases. Conclusion These results indicate that the mechanisms driving network recovery are more important than the immediate impact of disruption due to network recovery.

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Multilevel network interventions: Goals, actions, and outcomes

Cited by 8 publications

References 112 publications

Local Network Interaction as a Mechanism for Wealth Inequality

Local Network Interaction as a Mechanism for Wealth Inequality

Knowledge-driven networking and ambidextrous innovation equilibrium in power systems transition

Structural resilience and recovery of a criminal network after disruption: a simulation study

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