Integrating Multilevel Adaptive Models to Develop Systematic, Transparent, and Participatory EIA Practice

Andreea Nita*, Jan Treur, Laurentiu Rozylowicz

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

45 Downloads (Pure)


European Directive 85/337/EC introduced Environmental Impact Assessment (EIA) as a process governed by administrative rules with the aim of reducing environmental degradation and associated health problems generated by projects. Generally, the EIA process involves analyses and evaluations of the potential impacts that human activities may have on the environment by considering approaches such as the precautionary principle, prevention of conflicts, loss of natural resources, and environmental degradation. EIA influences decision-making at local, national, and transboundary levels, with the following overall objectives: potentially screen out environmentally harmful projects, predict significant adverse impacts, suggest measures to reduce or prevent major impacts, identify feasible alternatives, and engage communities or individuals potentially affected by the implementation of the project. Several issues obstructing the proper implementation of the EIA process are common in developing countries: low quality of assessment reports, lack of public participation, insufficient equipment, and trained staff, inadequate institutional framework, and low cooperation between policymakers, researchers, and stakeholders. The number of research studies focused on the investigation of EIA collaboration process through network analysis and multilevel adaptive models is worryingly limited, considering that the implementation of EIA procedures is deficient in most developing countries, and the contribution of science that envisages the collaboration between the actors involved to the process is minor at best. This paper aims to use Multilevel Network Reification to create Higher-order Adaptive Network Models. The results of multilevel network analysis will contribute to reshape impact assessment procedures and create opportunities for better communication and transparency between practitioners, researchers, policymakers, and other stakeholders. Therefore, integrating Multilevel Adaptive Models in EIA helps to raise the policy efficiency and define the dynamic interplay between EIA actors and diagnose the organizational structures that strongly influence this procedure. Thus, by using an adaptive computational network model, we aim to understand the roles of each actor and the connections established in different EIA networks. The findings will provide innovative information to find solutions and design a collaborative EIA procedure to improve projects under evaluation considering the current threats to society and the environment.

Original languageEnglish
Title of host publicationData Science and Intelligent Systems
Subtitle of host publicationProceedings of 5th Computational Methods in Systems and Software 2021, Vol. 2
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages19
ISBN (Electronic)9783030903213
ISBN (Print)9783030903206
Publication statusPublished - 2021
Event5th Computational Methods in Systems and Software, CoMeSySo 2021 - Virtual, Online
Duration: 1 Oct 20211 Oct 2021

Publication series

NameLecture Notes in Networks and Systems
Volume231 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


Conference5th Computational Methods in Systems and Software, CoMeSySo 2021
CityVirtual, Online

Bibliographical note

Funding Information:
Acknowledgment. AN and LR were supported by a grant of the Romanian National Authority for Scientific Research (, PN-III-P1-1.1-TE-2019-1039.

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.


  • Cooperation
  • EIA actors
  • Environmental impact assessment
  • Multilevel adaptive model
  • Nonadaptive model


Dive into the research topics of 'Integrating Multilevel Adaptive Models to Develop Systematic, Transparent, and Participatory EIA Practice'. Together they form a unique fingerprint.

Cite this