READ ME File For 'Perspectives of Academics, Prosecutors, Law enforcement agents, Journalists and other stakeholders on the trends of illegal investments in the UK real estate sector'

Dataset DOI: 10.5258/SOTON/D2396

ReadMe Author: Emanuele Sclafani, University of Southampton ORCID ID 0000-0002-8670-7511

This dataset supports the thesis entitled Investment of Criminal Proceeds into the Legitimate Economy: An Analysis of Italian and Russian Organised Crime in the UK Real Estate Market
AWARDED BY: University of Southampton
DATE OF AWARD: [2022]

DESCRIPTION OF THE DATA
The data collected for this academic investigation involves 22 semi-structured interviews conducted with academics who had international expertise and practitioners that were prosecutors, law enforcement agents, experts in financial investigations, lawyers, real estate community, investigative journalists, asset recovery experts, Non-governmental organisations (NGO), policy institutes/‘think tanks’. Before the data gathering started, relevant information on potential interviewees was collected via the internet, mass media publications, scholarly articles, and the websites of international organisations to select individuals who were directly or indirectly linked to the research topic from a legislative/criminological standpoint in order to create a matrix. The process of selecting interviewees was based on purposive sampling and snowball sampling. In the case of purposive sampling the interviewees were chosen as eligible for this study due to their rich knowledge of the investments of criminal proceeds in the UK real estate market. Snowball sampling, on the contrary, enabled me to access other groups of interviewees, through my initial participants. The participants in this study were accessed via e-mails/telephone calls/LinkedIn, through personal networks (through my legal and academic background) and through events such as conferences. After a brief introduction of the research if the participant showed an interest, date, time and location of the interview were fixed and the researcher provided interviewees with a participant information sheet and consent form via e-mail or in person. Only after understanding the full text of the participant information sheet and the consent form did the participant sign the consent form before the interview began. The interviews were audio-recorded as part of their consent. Interviews were conducted on a working day during working hours in the participant’s workplace, either face-to-face or via free online communication software. Interviews were conducted in an informal conversational manner in a quiet space where the participants felt comfortable to express their ideas and understanding of the phenomenon. The semi-structured interview started with general statement questions keeping the interview broad and flexible accompanied by an interview guide to help interviewer to steer the conversation to address the research questions. The nature of these questions was diversified based on the category the interviewee belonged to. The average length of interviews lasted from 35-45 minutes.  In this study the process involved collecting data from two different countries, the UK and Italy, through semi-structured interviews with multiple actors with first-hand knowledge on this research topic. The interviews were transcribed and uploaded on NVivo software for coding aim.

This dataset contains:
Consent form, participant information sheet and transcribed interviews conducted with prosecutors, law enforcement agents, experts in financial investigations, lawyers, real estate community, investigative journalists, asset recovery experts, Non-governmental organisations (NGO), policy institutes/‘think tanks’. 



Date of data collection: May 2019- May 2020

Information about geographic location of data collection: United Kingdom and Italy

Licence:
CC-BY

Related projects/Funders:
This PhD project has been partially funded by Fondazione Pol.i.s.- Politiche Integrate di Sicurezza (Italian Foundation, £3520 PhD scholarship) in 2018.

Date that the file was created: November, 2022