A diary study of information‐intensive work tasks in the modern workplace: Investigating task descriptions and task processes

Abstract The work‐task‐based framework offers a cohesive perspective for understanding workplace information behavior, guiding empirical exploration of information engagement in modern work environments. This study investigates both task descriptions and task processes of information‐intensive work tasks through diaries and follow‐up interviews to capture authentic user experiences. Data from 52 work tasks across diverse organizations reveal that the most frequent topics include Reference , Business , Science , Society , and Computers , with Intellectual and Decision/Solution product types being predominant. Performers typically begin with moderate or high work task knowledge. On average, each work task involves 2.5 seeking tasks and 5.3 search tasks. Seeking tasks are mainly linked to resolution‐oriented information use, while search tasks rely on external sources for factual resolution and verification. Work task topics, product, prior knowledge, subtasks, and duration significantly influence source selection and information use. As work tasks progress, the number of search tasks and clarification use decreases, whereas resolution and verification use increase. These findings refine theoretical models of task‐driven information behavior and provide practical insights for designing adaptive information systems and AI tools to better support evolving work task processes and enhance work performance.

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Publication Details

Journal
Journal of the Association for Information Science and Technology
Published
2025-11-14
DOI
https://doi.org/10.1002/asi.70037
Primary Topic
Personal Information Management and User Behavior
Type
article
Field-Weighted Citation Impact
0.00

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article

A diary study of information‐intensive work tasks in the modern workplace: Investigating task descriptions and task processes

Afeng Wang, Yiming Zhao, Feicheng Ma
Journal of the Association for Information Science and Technology
Personal Information Management and User Behavior
article

A diary study of information‐intensive work tasks in the modern workplace: Investigating task descriptions and task processes

Afeng Wang, Yiming Zhao, Feicheng Ma
article en

Abstract

Abstract The work‐task‐based framework offers a cohesive perspective for understanding workplace information behavior, guiding empirical exploration of information engagement in modern work environments. This study investigates both task descriptions and task processes of information‐intensive work tasks through diaries and follow‐up interviews to capture authentic user experiences. Data from 52 work tasks across diverse organizations reveal that the most frequent topics include Reference , Business , Science , Society , and Computers , with Intellectual and Decision/Solution product types being predominant. Performers typically begin with moderate or high work task knowledge. On average, each work task involves 2.5 seeking tasks and 5.3 search tasks. Seeking tasks are mainly linked to resolution‐oriented information use, while search tasks rely on external sources for factual resolution and verification. Work task topics, product, prior knowledge, subtasks, and duration significantly influence source selection and information use. As work tasks progress, the number of search tasks and clarification use decreases, whereas resolution and verification use increase. These findings refine theoretical models of task‐driven information behavior and provide practical insights for designing adaptive information systems and AI tools to better support evolving work task processes and enhance work performance.

Journal of the Association for Information Science and Technology
Wuhan University (CN), Suzhou Research Institute (CN), Wuhan Institute of Technology (CN)
National Natural Science Foundation of China, Ministry of Education of the People's Republic of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 67%
Personal Information Management and User Behavior
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