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Georesource production is part of the foundation of our modern society, yet obtaining the social licence to operate (SLO) is particularly complex. Such projects often attract strong public opposition (also known as NIMBY or BANANA attitudes). At the same time, the reasoning and, moreover, solution ideas of opposing individuals are little researched. This is partially due to the high complexity of quantifying reasoning during classic surveys. The rise of Generative AI (GenAI) provides the technological leap that allows us to survey the reasoning of individuals and quantify it in an economic way. The aim of this project is to explore the possibilities of GenAI-supported surveys to understand the reasoning and solution ideas of stakeholders and to obtain an outlook for improved stakeholder inclusion processes.
Research field: | Earth sciences |
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Supervisors: | Prof. Dr. Wolfgang Gerstlberger Bruno Grafe |
Availability: | This position is available. |
Offered by: | School of Science Department of Geology |
Application deadline: | Applications are accepted between June 01, 2025 00:00 and June 30, 2025 23:59 (Europe/Zurich) |
Supervisors
Duration of the project: 4 years (2025–2029)
Problem statement
Sentiment against resource extraction, be it primary or secondary, is at an all-time low in Estonia and the EU in general – although environmental standards are among the highest worldwide. Previous studies in Germany have further shown that sentiment against resource projects is dependent on the location of people surveyed: most negative in urban areas, most positive near mining areas; the less people know about mining, the more negative the sentiment is; knowledge about resources, how they are extracted, and their role in daily life is extremely limited. These problems are also known as Not-in-my-backyard (NIMBY), or more extreme, “Build absolutely nothing anywhere near anyone” (BANANA). However, resource projects require a “Social Licence to Operate” (SLO), which means that, irrespective of legal licences, the public does not oppose a project to the extent that operations are made impossible.
Surveys conducted in the field of mining and construction of large projects normally quantify the general sentiment on numerical scales but cannot capture the reasoning behind negative attitudes, the ideas of negatively opinionated individuals, let alone quantify these opinions and reasoning.
Solution and research approach
Semi-structured interviews allow for an assessment of reasoning behind pure opinion, but normally they have to be conducted by interviewers in person – limiting the application. However, the rise of GenAI has paved the way for analysing large amounts of free text and classifying responses in near-real time. This allows semi-interactive surveys that react to user responses and ask for reasoning and proposed solutions. Another aspect is the possibility to classify and bin free-text replies and the ability to quantify responses based on their similarity (similar to sentiment analysis). This allows for the quantification of large amounts of unstructured answers.
The project aims to investigate the possibilities and boundaries in the use of GenAI for these tasks, with a focus on the specific domain of the georesource industry, as this is one of the most negatively viewed industries.
Aims
The objectives of this PhD project are to:
Responsibilities
The project will include:
Requirements and beneficial experiences
We offer
TalTech Department of Geology
The Department of Geology is the centre of expertise in geology, mineral resources, and mining at TalTech. Our researchers focus on bedrock geology, paleoenvironments, mineral resources, mining engineering and circular economy. We are responsible for study programmes on Earth systems and resources and host various labs and the largest geoscience collections in Estonia.
TalTech Department of Business Administration - Sustainable Value Chain Management Research Group
Sustainable value chain management focuses on preparing and supporting innovation and growth within a firm’s strategic framework. The research group explores these opportunities using interdisciplinary methods from business, sustainability (e.g., Circular Economy), environmental economics, engineering, IT, design, and social sciences. Emphasis is placed on digitalization, smart production, Industry 4.0, Big Data, and strategic networks, aligned with Europe’s smart, sustainable, and inclusive growth agenda. Projects are typically conducted in cooperation with businesses and supported by European or national initiatives.
To get more information or to apply online, visit https://taltech.glowbase.com/positions/1004 or scan the code on the left with your smartphone.
Tallinn University of Technology (TalTech) is the only flagship in engineering and IT science and education in Estonia.
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