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Open Access
Article
Publication date: 27 March 2023

Annye Braca and Pierpaolo Dondio

Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine…

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Abstract

Purpose

Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

Design/methodology/approach

A total of 1,022 individuals took part in the survey; participants were asked to fill out the ten item personality measure questionnaire to capture personality traits and the dysfunctional attitude scale (DAS) to measure dysfunctional beliefs and cognitive vulnerabilities. ML classification models using participant profiling information as input were developed to predict the extent to which an individual was influenced by statements that contained different linguistic styles/persuasion techniques. Several ML algorithms were used including support vector machine, LightGBM and Auto-Sklearn to predict the effect of each technique given each individual’s profile (personality, belief system and demographic data).

Findings

The findings highlight the importance of incorporating emotion-based variables as model input in predicting the influence of textual statements with embedded persuasion techniques. Across all investigated models, the influence effect could be predicted with an accuracy ranging 53%–70%, indicating the importance of testing multiple ML algorithms in the development of a persuasive communication (PC) system. The classification ability of models was highest when predicting the response to statements using rhetorical devices and flattery persuasion techniques. Contrastingly, techniques such as authority or social proof were less predictable. Adding DAS scale features improved model performance, suggesting they may be important in modelling persuasion.

Research limitations/implications

In this study, the survey was limited to English-speaking countries and largely Western society values. More work is needed to ascertain the efficacy of models for other populations, cultures and languages. Most PC efforts are targeted at groups such as users, clients, shoppers and voters with this study in the communication context of education – further research is required to explore the capability of predictive ML models in other contexts. Finally, long self-reported psychological questionnaires may not be suitable for real-world deployment and could be subject to bias, thus a simpler method needs to be devised to gather user profile data such as using a subset of the most predictive features.

Practical implications

The findings of this study indicate that leveraging richer profiling data in conjunction with ML approaches may assist in the development of enhanced persuasive systems. There are many applications such as online apps, digital advertising, recommendation systems, chatbots and e-commerce platforms which can benefit from integrating persuasion communication systems that tailor messaging to the individual – potentially translating into higher economic returns.

Originality/value

This study integrates sets of features that have heretofore not been used together in developing ML-based predictive models of PC. DAS scale data, which relate to dysfunctional beliefs and cognitive vulnerabilities, were assessed for their importance in identifying effective persuasion techniques. Additionally, the work compares a range of persuasion techniques that thus far have only been studied separately. This study also demonstrates the application of various ML methods in predicting the influence of linguistic styles/persuasion techniques within textual statements and show that a robust methodology comparing a range of ML algorithms is important in the discovery of a performant model.

Details

Journal of Systems and Information Technology, vol. 25 no. 2
Type: Research Article
ISSN: 1328-7265

Keywords

Open Access
Article
Publication date: 18 February 2021

Maddy Power, Katie J. Pybus, Kate E. Pickett and Bob Doherty

Background: Evidence suggests that people living in poverty often experience inadequate nutrition with short and long-term health consequences. Whilst the diets of low-income…

Abstract

Background: Evidence suggests that people living in poverty often experience inadequate nutrition with short and long-term health consequences. Whilst the diets of low-income households have been subject to scrutiny, there is limited evidence in the UK on the diet quality and food practices of households reporting food insecurity and food bank use. We explore lived experiences of food insecurity and underlying drivers of diet quality among low-income families, drawing upon two years of participatory research with families of primary school age children.

Methods: We report on a mixed-methods study of the relationship between low income, food bank use, food practices and consumption from a survey of 612 participants, including 136 free text responses and four focus groups with 22 participants. The research followed a parallel mixed-methods design: qualitative and quantitative data were collected separately, although both were informed by participatory work. Quantitative data were analysed using binary and multinomial logistic regression modelling; qualitative data were analysed thematically.

Results: Lower income households and those living with food insecurity struggle to afford a level of fruit and vegetable consumption that approaches public health guidance for maintaining a healthy diet, despite high awareness of the constituents of a healthy diet. Participants used multiple strategies to ensure as much fruit, vegetable and protein consumption as possible within financial constraints. The quantitative data suggested a relationship between higher processed food consumption and having used a food bank, independent of income and food security status.

Conclusions: The findings suggest that individualised, behavioural accounts of food practices on a low-income misrepresent the reality for people living with poverty. Behavioural or educational interventions are therefore likely to be less effective in tackling food insecurity and poor nutrition among people on a low income; policies focusing on structural drivers, including poverty and geographical access to food, are needed.

Details

Emerald Open Research, vol. 1 no. 10
Type: Research Article
ISSN: 2631-3952

Keywords

Open Access
Article
Publication date: 1 November 2021

Rita Jeanne Shea-Van Fossen, Rosa Di Virgilio Taormina and JoDee LaCasse

The purpose of this paper is to determine which software systems business school administrators use to support accreditation efforts and how administrators select and use these…

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Abstract

Purpose

The purpose of this paper is to determine which software systems business school administrators use to support accreditation efforts and how administrators select and use these systems. This study also provides best practice suggestions from institutions using faculty data management systems to support accreditation efforts.

Design/methodology/approach

This study used a sequential explanatory design using an internet-based survey for business school administrators involved with accreditation reporting with follow-up interviews with survey respondents.

Findings

There are four major software vendors that most respondents use for managing reporting of faculty research activity and sufficiency. The location of the school appears to influence the system selected. For assurance of learning reporting, most schools used an in-house or manual system. Respondents highlighted the importance of doing a thorough needs analysis before selecting a system.

Research limitations/implications

Although respondents were geographically diverse, having a larger sample with schools in developing regions would provide greater generalizability of results.

Practical implications

This study gives business school leaders a comprehensive overview of the business schools’ data management systems, criteria used in system selection and best practices for system selection and implementation, faculty engagement and ongoing maintenance.

Originality/value

This study addresses the limited attention given to resources and best practices for selecting and implementing faculty data management software for accreditation in the academic and industry literature despite the significant investment of resources for schools and the importance such systems play in a successful accreditation effort.

Details

Organization Management Journal, vol. 18 no. 5
Type: Research Article
ISSN: 1541-6518

Keywords

Open Access
Article
Publication date: 12 February 2020

Matthew Hanchard, Peter Merrington, Bridgette Wessels, Kathy Rogers, Michael Pidd, Simeon Yates, David Forrest, Andrew Higson, Nathan Townsend and Roderik Smits

In this article, we discuss an innovative audience research methodology developed for the AHRC-funded “Beyond the Multiplex: Audiences for Specialised Film in English Regions”…

Abstract

In this article, we discuss an innovative audience research methodology developed for the AHRC-funded “Beyond the Multiplex: Audiences for Specialised Film in English Regions” project (BtM). The project combines a computational ontology with a mixed-methods approach drawn from both the social sciences and the humanities, enabling research to be conducted both at scale and in depth, producing complex relational analyses of audiences. BtM aims to understand how we might enable a wide range of audiences to participate in a more diverse film culture, and embrace the wealth of films beyond the mainstream in order to optimise the cultural value of engaging with less familiar films. BtM collects data through a three-wave survey of film audience members’ practices, semi-structured interviews and film-elicitation groups with audience members alongside interviews with policy and industry experts, and analyses of key policy and industry documents. Bringing each of these datasets together within our ontology enables us to map relationships between them across a variety of different concerns. For instance, how cultural engagement in general relates to engagement with specialised films; how different audiences access and/or share films across different platforms and venues; how their engagement with those films enables them to make meaning and generate value; and how all of this is shaped by national and regional policy, film industry practices, and the decisions of cultural intermediaries across the fields of film production, distribution and exhibition. Alongside our analyses, the ontology enables us to produce data visualisations and a suite of analytical tools for audience development studies that stakeholders can use, ensuring the research has impact beyond the academy. This paper sets out our methodology for developing the BtM ontology, so that others may adapt it and develop their own ontologies from mixed-methods empirical data in their studies of other knowledge domains.

Details

Emerald Open Research, vol. 1 no. 1
Type: Research Article
ISSN: 2631-3952

Keywords

Open Access
Article
Publication date: 21 January 2021

Marcus Bengtsson, Lars-Gunnar Andersson and Pontus Ekström

The purpose of the study is to test if it, by the use of a survey methodology, is possible to measure managers' awareness on, and specifically if there exist preconceived beliefs…

1980

Abstract

Purpose

The purpose of the study is to test if it, by the use of a survey methodology, is possible to measure managers' awareness on, and specifically if there exist preconceived beliefs on, overall equipment effectiveness (OEE) results. The paper presents the design of the survey methodology as well as a test of the survey in one case company.

Design/methodology/approach

Actual OEE logs from a case company are collected and a survey on the data is designed and managers at the same case company are asked to answer the survey. The survey results are followed-up by an interview study in order to get deeper insights to both the results of the survey as well as the OEE strategy at the case company.

Findings

The findings show that the managers at this particular case company, on a general level, does not suffer too much from preconceived beliefs. However, it is clear that the managers have a preconceived belief that lack of material is logged as a loss much more often than what it actually is.

Research limitations/implications

The test has only been performed with data from one case company within the automotive manufacturing industry and only the managers at that case company has been active in the test.

Practical implications

The survey methodology can be replicated and used by other companies to find out how aware their employees are on their OEE results and if possible preconceived beliefs exists.

Originality/value

To the authors' knowledge, this is the first attempt at measuring if preconceived beliefs on OEE results exist.

Details

Journal of Quality in Maintenance Engineering, vol. 28 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

Open Access
Article
Publication date: 6 September 2019

Andrew M. Cox, Mary Anne Kennan, Liz Lyon, Stephen Pinfield and Laura Sbaffi

A major development in academic libraries in the last decade has been recognition of the need to support research data management (RDM). The purpose of this paper is to capture…

8343

Abstract

Purpose

A major development in academic libraries in the last decade has been recognition of the need to support research data management (RDM). The purpose of this paper is to capture how library research data services (RDS) have developed and to assess the impact of this on the nature of academic libraries.

Design/methodology/approach

Questionnaire responses from libraries in Australia, Canada, Germany, Ireland, the Netherlands, New Zealand, the UK and USA from 2018 are compared to a previous data set from 2014.

Findings

The evidence supports a picture of the spread of RDS, especially advisory ones. However, future ambitions do not seem to have seen much evolution. There is limited evidence of organisational change and skills shortages remain. Most service development can be explained as the extension of traditional library services to research data. Yet there remains the potential for transformational impacts, when combined with the demands implied by other new services such as around text and data mining, bibliometrics and artificial intelligence. A revised maturity model is presented that summarises typical stages of development of services, structures and skills.

Research limitations/implications

The research models show how RDS are developing. It also reflects on the extent to which RDM represents a transformation of the role of academic libraries.

Practical implications

Practitioners working in the RDM arena can benchmark their current practices and future plans against wider patterns.

Originality/value

The study offers a clear picture of the evolution of research data services internationally and proposes a maturity model to capture typical stages of development. It contributes to the wider discussion of how the nature of academic libraries are changing.

Details

Journal of Documentation, vol. 75 no. 6
Type: Research Article
ISSN: 0022-0418

Keywords

Content available
Article
Publication date: 1 March 2005

Karl Wennberg

This article provides an account of how databases can be effectively used in entrepreneurship research. Improved quality and access to large secondary databases offer paths to…

1254

Abstract

This article provides an account of how databases can be effectively used in entrepreneurship research. Improved quality and access to large secondary databases offer paths to answer questions of great theoretical value. I present an overview of theoretical, methodological, and practical difficulties in working with database data, together with advice on how such difficulties can be overcome. Conclusions are given, together with suggestions of areas where databases might provide real and important contributions to entrepreneurship research.

Details

New England Journal of Entrepreneurship, vol. 8 no. 2
Type: Research Article
ISSN: 2574-8904

Open Access
Article
Publication date: 12 November 2019

Andy Nobes and Siân Harris

Open access (OA) is often considered as particularly beneficial to researchers in the global south. However, research into awareness of and attitudes to OA has been largely…

Abstract

Open access (OA) is often considered as particularly beneficial to researchers in the global south. However, research into awareness of and attitudes to OA has been largely dominated by voices from the global north. A survey was conducted of 507 researchers from the developing world and connected to INASP's AuthorAID project to ascertain experiences and attitudes to OA publishing. The survey revealed problems for the researchers in gaining access to research literature in the first place. There was a very positive attitude to OA research and OA journals, but when selecting a journal in which to publish, OA was seen as a much less important criterion than factors relating to international reputation. Overall, a majority of respondents had published in an OA journal and most of these had paid an article processing charge. Knowledge and use of self-archiving via repositories varied, and only around 20% had deposited their research in an institutional repository. The study also examined attitudes to copyright, revealing most respondents had heard of Creative Commons licences and were positive about the sharing of research for educational use and dissemination, but there was unease about research being used for commercial purposes. Respondents revealed a surprisingly positive stance towards openly sharing research data, although many revealed that they would need further guidance on how to do so. The survey also revealed that the majority had received emails from so called “predatory” publishers and that a small minority had published in them.

Details

Emerald Open Research, vol. 1 no. 3
Type: Research Article
ISSN: 2631-3952

Keywords

Open Access
Article
Publication date: 7 December 2021

Jeannette Waegemakers Schiff, Eric Paul Weissman, Deborah Scharf, Rebecca Schiff, Stephanie Campbell, Jordan Knapp and Alana Jones

This paper aims to discuss the challenges of conducting research with homelessness services frontline workers during the COVID-19 pandemic.

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Abstract

Purpose

This paper aims to discuss the challenges of conducting research with homelessness services frontline workers during the COVID-19 pandemic.

Design/methodology/approach

Between 2015 and 2019, the research team surveyed frontline staff in three cities about their psychosocial stressors and needs. In 2020, the authors replicated the previous study and expanded data collection to seven cities across Canada to determine the extent to which the COVID-19 pandemic impacted the well-being of frontline staff. This report describes how the authors adapted the research methodologies to continue work throughout the pandemic, despite various restrictions.

Findings

The original studies had very high participation rates because of several methodological approaches that minimized barriers, especially in-person data collection. During the pandemic, distancing requirements precluded replication of these same methods. Research strategies that enabled staff participation during working hours, with designated time allotted for participation, was key for ensuring high participation rates, as access to technology, availability of free time and other factors frequently make online survey research a hardship for these staff. Restrictive interpretation and regional variations of COVID-19 guidelines by some research ethics boards were also a challenge to rapid and responsive data collection.

Originality/value

Few studies describe the experiences of frontline workers in the homelessness sector, and quantitative reports of their experiences are particularly scant. Consequently, little is known about specific methodologies that facilitate large-scale data collection in the homelessness services sector. The present research advances the field by providing lessons learned about best practice approaches in pre and post COVID-19 front line worker contexts. A strength of this research is the well-controlled design. The authors collected data within several of the organizations that had previously participated. This fortunate baseline provided opportunity for comparison before and during the pandemic; the authors can highlight factors that might have had influence during the pandemic.

Details

Housing, Care and Support, vol. 24 no. 3/4
Type: Research Article
ISSN: 1460-8790

Keywords

Open Access
Article
Publication date: 24 October 2022

Suzana Sukovic, Jamaica Eisner and Kerith Duncanson

Effective use of data across public health organisations (PHOs) is essential for the provision of health services. While health technology and data use in clinical practice have…

Abstract

Purpose

Effective use of data across public health organisations (PHOs) is essential for the provision of health services. While health technology and data use in clinical practice have been investigated, interactions with data in non-clinical practice have been largely neglected. The purpose of this paper is to consider what constitutes data, and how people in non-clinical roles in a PHO interact with data in their practice.

Design/methodology/approach

This mixed methods study involved a qualitative exploration of how employees of a large PHO interact with data in their non-clinical work roles. A quantitative survey was administered to complement insights gained through qualitative investigation.

Findings

Organisational boundaries emerged as a defining issue in interactions with data. The results explain how data work happens through observing, spanning and shifting of boundaries. The paper identifies five key issues that shape data work in relation to boundaries. Boundary objects and processes are considered, as well as the roles of boundary spanners and shifters.

Research limitations/implications

The study was conducted in a large Australian PHO, which is not completely representative of the unique contexts of similar organisations. The study has implications for research in information and organisational studies, opening fields of inquiry for further investigation.

Practical implications

Effective systems-wide data use can improve health service efficiencies and outcomes. There are also implications for the provision of services by other health and public sectors.

Originality/value

The study contributes to closing a significant research gap in understanding interactions with data in the workplace, particularly in non-clinical roles in health. Research analysis connects concepts of knowledge boundaries, boundary spanning and boundary objects with insights into information behaviours in the health workplace. Boundary processes emerge as an important concept to understand interactions with data. The result is a novel typology of interactions with data in relation to organisational boundaries.

Details

Global Knowledge, Memory and Communication, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9342

Keywords

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