article

24-hour knowledge factory: Using Internet technology to leverage spatial and temporal separations

Authors:

Satwik SeshasaiAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 7, Issue 3

Pages 14 - es

https://doi.org/10.1145/1275505.1275507

Published: 01 August 2007 Publication History

Abstract

Several of the outsourcing endeavors of today will gradually converge to a hybrid outsourcing model that will involve a team spread across three or more strategically-located centers interconnected by Internet technology. White-collar professionals in the US, Australia, and Poland, for example, could each work on a standard 9--5 basis, transfer the activity to a colleague in the next center, thereby enabling work to be performed on a round-the-clock basis. The effective use of sequential workers in such a 24-hour knowledge factory requires that professional tasks be broken down to the level where individuals can work on them with minimal interaction with their peers, and where new approaches can be employed to reduce the effort involved in transitioning from one employee to the next. This article describes an Internet-based prototype system that uses a Web-based interactive approach, coupled with a unique data model, to optimize collection and storage of design rationale and history from stakeholders and workers. The idea of multiple individuals acting as one “composite persona” is explored in the context of facilitating tasks and knowledge to be shared across the Internet in a seamless manner. The article also describes related activities in the commercial arena.

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24-hour knowledge factory: Using Internet technology to leverage spatial and temporal separations

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Published In

cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 7, Issue 3

Special Issue on the Internet and Outsourcing

August 2007

97 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/1275505

Issue’s Table of Contents

Copyright © 2007 ACM.

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Publication History

Published: 01 August 2007

Published in TOIT Volume 7, Issue 3

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https://doi.org/10.1109/EICEEAI60672.2023.10590129
Djenouri YBelhadi ADjenouri DSrivastava GLin J(2022)Intelligent Deep Fusion Network for Anomaly Identification in Maritime Transportation SystemsIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2022.3151490(1-9)Online publication date: 2022
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