Network formation in organizational settings: Exploring the importance of local social processes and team-level contextual variables in small groups using bayesian hierarchical ERGMs-Reference-Cited by-同舟云学术

Network formation in organizational settings: Exploring the importance of local social processes and team-level contextual variables in small groups using bayesian hierarchical ERGMs

Published:2022-08 Issue: Volume: Page:
ISSN:0378-8733
Container-title:Social Networks
language:en
Short-container-title:Social Networks

Author:

Agneessens Filip,Trincado-Munoz Francisco J.,Koskinen Johan

Publisher

Elsevier BV

Subject

General Psychology,General Social Sciences,Sociology and Political Science,Anthropology

Reference121 articles.

1. Dyadic, Nodal, and Group-Level Approaches to Study the Antecedents and Consequences of Networks.;Agneessens,2020

2. Modeling individual outcomes using a multilevel social influence (MSI) model: Individual versus team effects of trust on job satisfaction in an organisational context;Agneessens,2016

3. Collecting survey-based social network information in work organizations;Agneessens;Soc. Netw.,2022

4. The effect of propensity to trust and perceptions of trustworthiness on trust behaviors in dyads;Alarcon;Behav. Res. Methods,2018

5. Large-scale estimation of random graph models with local dependence;Babkin;Comput. Stat. Data Anal.,2020

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Nascent policy subsystems in polycentric governance networks: The case of sea‐level rise governance in the San Francisco Bay Area;Policy Studies Journal;2024-07-15

2. Cross-sectional social network study of adolescent peer group variation in substance use and mental wellbeing: The importance of the meso level;Social Networks;2024-07

3. Same but different;Social Networks;2024-01

4. Status, cognitive overload, and incomplete information in advice-seeking networks: An agent-based model;Social Networks;2024-01

5. Scaling bias in pooled exponential random graph models;Social Networks;2023-07