Search results

1 – 3 of 3
Article
Publication date: 7 May 2024

Richard Kapend, Mark Button and Peter Stiernstedt

A significant number of criminal and deviant acts are investigated by nonpolice actors. These include private investigators who charge fees for their services, professional…

Abstract

Purpose

A significant number of criminal and deviant acts are investigated by nonpolice actors. These include private investigators who charge fees for their services, professional services firms such as firms of accountants who also charge fees, in-house investigators employed by private organisations and in-house investigators of public sector organisations who are not sworn police officers. Some of these investigators, such as private investigators, have been exposed in unethical activities such as illegal surveillance and blagging to name some. In this respect, this study aims to uncover the ethical orientations of investigators using cluster analysis.

Design/methodology/approach

This study is based upon an online survey of private investigators predominantly in the UK, i.e. investigators beyond the public police. An innovate statistical inferential analysis was used to investigate the sample which resulted in the development of three ethical orientations of such investigators.

Findings

Based upon a survey response from 331 of these types of investigators this study illustrates the extent they engage in unethical activities, showing a very small minority of largely private investigators who engage in such activities.

Originality/value

A unique feature of this study is the use of an innovative statistical approach using an unsupervised machine learning model, namely, TwoStep cluster analysis, to successfully group and classify respondents based on their ethical orientation. The model derived three types of ethical orientation: ethical, inbetweeners and risk takers.

Details

Journal of Financial Crime, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1359-0790

Keywords

Article
Publication date: 29 March 2024

Jiming Hu, Zexian Yang, Jiamin Wang, Wei Qian, Cunwan Feng and Wei Lu

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the…

Abstract

Purpose

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

Design/methodology/approach

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Findings

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

Research limitations/implications

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Practical implications

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

Social implications

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

Originality/value

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 16 September 2024

Hongfei Liu, Yue Meng-Lewis and Wentong Liu

Social media played an irreplaceable role in young people’s online social life and information consumption during the COVID-19 pandemic. This research focuses on the impact of…

Abstract

Purpose

Social media played an irreplaceable role in young people’s online social life and information consumption during the COVID-19 pandemic. This research focuses on the impact of excessive information on social media about COVID-19 vaccines on Generation Z's (Gen Z) associated psychological states and long-term vaccine advocacy.

Design/methodology/approach

The research conducted structural equation modeling analysis with online survey data from 409 Gen Z citizens in the UK.

Findings

The findings suggest that excessive information increased Gen Z social media users' ambivalence and conspiracy beliefs around COVID-19 vaccines, which, in turn, reduced their long-term vaccine advocacy in terms of vaccine acceptance, vaccination intention and vaccine promotion. Importantly, Gen Z’s confidence in government and in the healthcare systems during COVID-19 was effective in helping them overcome the detrimental effects of conspiracy beliefs and ambivalence about long-term vaccine advocacy, respectively.

Originality/value

This research reveals the “dark side” of social media use in the post-pandemic period and highlights the significant roles played by social institutions in mitigating the detrimental effects of Gen Z’s support in social decisions. Beyond the context of COVID-19, this research has important implications for facilitating the civic engagement of Gen Z and boosting their confidence in social institutions in terms of social cohesion.

Details

Information Technology & People, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-3845

Keywords

1 – 3 of 3