Enhancing IT Service Desk for Hybrid Work: Insight from a TOE and TTF Case Study

Adopting hybrid work has brought new challenges of IT service desks in small companies with limited resources. This study focuses on a software company in Jakarta with 15 employees, exploring how its size influences the ability to resolve issues, manage tickets, and keep both remote and on-site staff satisfied. Utilizing the Technology-Organization-Environment (TOE) Framework and the Task-Technology Fit (TTF) Model, we investigated ticket records, surveyed 13 employees, and conducted group discussions for deeper analysis. On average, the initial response time was 3.5 hours, but remote staff often faced slower resolutions, averaging 3.8 hours compared to 3.2 hours for on-site employees. The most common problems were connectivity issues, which made up 40 percent of tickets, and login and access challenges, which made up 30 percent. Feedback from a Survey indicated moderate satisfaction with most ratings between 3 and 4 on a 1–5 scale, with gaps in communication and guidance, particularly for remote workers being identified. We suggest refined troubleshooting, enhanced communications, and simplified tracking methods for monitoring issues (real time) to overcome these challenges. These improvements may allow small businesses to make the most of IT support, minimize recurring issues and better accommodate hybrid workplace needs.

Authors

Institutions

Publication Details

Journal
Journal of Information Systems and Informatics
Published
2025-03-28
DOI
https://doi.org/10.51519/journalisi.v7i1.971
Primary Topic
Service-Oriented Architecture and Web Services
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing IT Service Desk for Hybrid Work: Insight from a TOE and TTF Case Study

Marcel Marcel, Garpepi Hanief Aotearoa
Journal of Information Systems and Informatics
Service-Oriented Architecture and Web Services
article

Enhancing IT Service Desk for Hybrid Work: Insight from a TOE and TTF Case Study

Marcel Marcel, Garpepi Hanief Aotearoa
article en

Abstract

Adopting hybrid work has brought new challenges of IT service desks in small companies with limited resources. This study focuses on a software company in Jakarta with 15 employees, exploring how its size influences the ability to resolve issues, manage tickets, and keep both remote and on-site staff satisfied. Utilizing the Technology-Organization-Environment (TOE) Framework and the Task-Technology Fit (TTF) Model, we investigated ticket records, surveyed 13 employees, and conducted group discussions for deeper analysis. On average, the initial response time was 3.5 hours, but remote staff often faced slower resolutions, averaging 3.8 hours compared to 3.2 hours for on-site employees. The most common problems were connectivity issues, which made up 40 percent of tickets, and login and access challenges, which made up 30 percent. Feedback from a Survey indicated moderate satisfaction with most ratings between 3 and 4 on a 1–5 scale, with gaps in communication and guidance, particularly for remote workers being identified. We suggest refined troubleshooting, enhanced communications, and simplified tracking methods for monitoring issues (real time) to overcome these challenges. These improvements may allow small businesses to make the most of IT support, minimize recurring issues and better accommodate hybrid workplace needs.

Journal of Information Systems and InformaticsVol. 7(1)
Krida Wacana Christian University (ID)
Openalex Percentile: Top 90%
Service-Oriented Architecture and Web Services
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.