Behavioural Predictors that Influence Digital Legacy Management Intentions among Individuals in South Africa

Fuente: arXiv
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Autores principales: Young, Jordan, Pekane, Ayanda, Kautondokwa, Popyeni
Formato: Preprint
Publicado: 2025
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author Young, Jordan
Pekane, Ayanda
Kautondokwa, Popyeni
author_facet Young, Jordan
Pekane, Ayanda
Kautondokwa, Popyeni
contents An emerging phenomenon, digital legacy management explores the management of digital data individuals accumulate throughout their lifetime. With the integration of digital systems and data into people's daily lives, it becomes crucial to understand the intricacies of managing data to eventually form one's digital legacy. This can be understood by investigating the significance of behavioral predictors in shaping digital legacy management. The objective of this study is to explore how behavioral predictors influence the intentions of individuals in South Africa towards managing their digital legacy. This entailed: Investigating the impact of attitude, subjective norms, and perceived behavioral control on these intentions. Exploring the perceived usefulness of digital legacy management systems. Understanding the implications of response cost and task-technology fit on individuals' inclinations towards digital legacy planning. Data were collected (n = 203 valid responses) from South African residents using an online survey and analyzed using partial least squares structural equation analysis (PLS-SEM). Results indicate that attitudes, peer opinions, personal resources, and skills are significant positive influences on digital legacy management intention. Recognizing and understanding these behavioral predictors is key when developing region-specific and culturally sensitive digital legacy management tools, awareness campaigns, and policies. Furthermore, it could pave the way for more tailored strategies, ensuring effective transfer of post-mortem data, reducing potential conflicts, and providing clarity when dealing with post-mortem data.
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id arxiv_https___arxiv_org_abs_2502_18542
institution arXiv
publishDate 2025
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spellingShingle Behavioural Predictors that Influence Digital Legacy Management Intentions among Individuals in South Africa
Young, Jordan
Pekane, Ayanda
Kautondokwa, Popyeni
Computers and Society
Digital Libraries
An emerging phenomenon, digital legacy management explores the management of digital data individuals accumulate throughout their lifetime. With the integration of digital systems and data into people's daily lives, it becomes crucial to understand the intricacies of managing data to eventually form one's digital legacy. This can be understood by investigating the significance of behavioral predictors in shaping digital legacy management. The objective of this study is to explore how behavioral predictors influence the intentions of individuals in South Africa towards managing their digital legacy. This entailed: Investigating the impact of attitude, subjective norms, and perceived behavioral control on these intentions. Exploring the perceived usefulness of digital legacy management systems. Understanding the implications of response cost and task-technology fit on individuals' inclinations towards digital legacy planning. Data were collected (n = 203 valid responses) from South African residents using an online survey and analyzed using partial least squares structural equation analysis (PLS-SEM). Results indicate that attitudes, peer opinions, personal resources, and skills are significant positive influences on digital legacy management intention. Recognizing and understanding these behavioral predictors is key when developing region-specific and culturally sensitive digital legacy management tools, awareness campaigns, and policies. Furthermore, it could pave the way for more tailored strategies, ensuring effective transfer of post-mortem data, reducing potential conflicts, and providing clarity when dealing with post-mortem data.
title Behavioural Predictors that Influence Digital Legacy Management Intentions among Individuals in South Africa
topic Computers and Society
Digital Libraries
url https://arxiv.org/abs/2502.18542