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Article
Publication date: 17 June 2024

Arushi Bathla, Ginni Chawla, Mahrane Hofaidhllaoui and Marina Dabic

Applying critical analysis as the methodological framework for assessing the literature, the review seeks to present a summary and evaluation of the existing body of knowledge…

Abstract

Purpose

Applying critical analysis as the methodological framework for assessing the literature, the review seeks to present a summary and evaluation of the existing body of knowledge. This approach helps to establish the basis for developing forthcoming recommendations.

Design/methodology/approach

The articles were selected through a Systematic Literature Review following the PRISMA guidelines, and utilising Scopus, Web of Science, Science Direct, and the Education Resources Information Center database. Field taxonomy is presented based on the outcomes.

Findings

Through a critical review, we offer narrative arguments that document the shortcomings in the existing literature by scrutinising study designs and highlighting suboptimal approaches. Finally, we issue a call to action for future research, envisioning its potential to reorient and reconstruct the field while enhancing the quality of future studies. This proactive stance aims to foster the development of more competent and insightful perspectives, theories, and policy recommendations within design thinking in management education and training.

Practical implications

The research in this field holds significant potential for providing valuable practical and policy insights, contingent upon the rigorous and thorough execution of studies.

Originality/value

This article presents a robust critical review of 57 state-of-the-art articles investigating design thinking in the context of management education and training.

Details

European Journal of Innovation Management, vol. 27 no. 9
Type: Research Article
ISSN: 1460-1060

Keywords

Article
Publication date: 11 October 2022

Tianjie Deng, Anamika Barman-Adhikari, Young Jin Lee, Rinku Dewri and Kimberly Bender

This study investigates associations between Facebook (FB) conversations and self-reports of substance use among youth experiencing homelessness (YEH). YEH engage in high rates of…

Abstract

Purpose

This study investigates associations between Facebook (FB) conversations and self-reports of substance use among youth experiencing homelessness (YEH). YEH engage in high rates of substance use and are often difficult to reach, for both research and interventions. Social media sites provide rich digital trace data for observing the social context of YEH's health behaviors. The authors aim to investigate the feasibility of using these big data and text mining techniques as a supplement to self-report surveys in detecting and understanding YEH attitudes and engagement in substance use.

Design/methodology/approach

Participants took a self-report survey in addition to providing consent for researchers to download their Facebook feed data retrospectively. The authors collected survey responses from 92 participants and retrieved 33,204 textual Facebook conversations. The authors performed text mining analysis and statistical analysis including ANOVA and logistic regression to examine the relationship between YEH's Facebook conversations and their substance use.

Findings

Facebook posts of YEH have a moderately positive sentiment. YEH substance users and non-users differed in their Facebook posts regarding: (1) overall sentiment and (2) topics discussed. Logistic regressions show that more positive sentiment in a respondent's FB conversation suggests a lower likelihood of marijuana usage. On the other hand, discussing money-related topics in the conversation increases YEH's likelihood of marijuana use.

Originality/value

Digital trace data on social media sites represent a vast source of ecological data. This study demonstrates the feasibility of using such data from a hard-to-reach population to gain unique insights into YEH's health behaviors. The authors provide a text-mining-based toolkit for analyzing social media data for interpretation by experts from a variety of domains.

Details

Information Technology & People, vol. 36 no. 6
Type: Research Article
ISSN: 0959-3845

Keywords

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