Heterogeneous agent-enabled decision system for evaluating Green IT performance in industrial environments
This article implements heterogeneous agent-enabled decision systems that provide a Green IT nomenclature to be implemented by IT practitioners in an industrial environment. Moreover, the system evaluates and ranks the current Green IT performance in an industrial environment. Data was collected usi...
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2018
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my.ump.umpir.215702018-09-12T07:55:42Z http://umpir.ump.edu.my/id/eprint/21570/ Heterogeneous agent-enabled decision system for evaluating Green IT performance in industrial environments Bokolo, Anthony Jnr Mazlina, Abdul Majid Awanis, Romli H Social Sciences (General) This article implements heterogeneous agent-enabled decision systems that provide a Green IT nomenclature to be implemented by IT practitioners in an industrial environment. Moreover, the system evaluates and ranks the current Green IT performance in an industrial environment. Data was collected using questionnaire from selected industries in Malaysia and analyzed using Statistical Package for Social Science (SPSS) by applying descriptive and factor analysis to test the usability of the agentbased evaluating system. Respectively, findings from this study indicate that the heterogeneous agents facilitate decision-making of IT practitioners by providing information on how they improve their current Green IT practice towards addressing environmental issues. Besides, the system reduces the time and cost of Green IT practice implementation by capturing, retaining and reusing past knowledge for improved decisionmaking. Practically, the system provides decision support by providing best-practice recommendations to IT practitioners on Green IT nomenclature to be implemented in their industrial operations. Taylor & Francis 2018-01-29 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/21570/1/6.pdf Bokolo, Anthony Jnr and Mazlina, Abdul Majid and Awanis, Romli (2018) Heterogeneous agent-enabled decision system for evaluating Green IT performance in industrial environments. Journal of Decision Systems, 27 (1). pp. 37-62. ISSN 1246-0125 https://doi.org/10.1080/12460125.2018.1490550 10.1080/12460125.2018.1490550 |
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H Social Sciences (General) Bokolo, Anthony Jnr Mazlina, Abdul Majid Awanis, Romli Heterogeneous agent-enabled decision system for evaluating Green IT performance in industrial environments |
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This article implements heterogeneous agent-enabled decision systems that provide a Green IT nomenclature to be implemented by IT practitioners in an industrial environment. Moreover, the system evaluates and ranks the current Green IT performance in an industrial environment. Data was collected using questionnaire from selected industries in Malaysia and analyzed using Statistical Package for Social Science (SPSS) by applying descriptive and factor analysis to test the usability of the agentbased evaluating system. Respectively, findings from this study indicate that the heterogeneous agents facilitate decision-making of IT practitioners by providing information on how they improve their current Green IT practice towards addressing environmental issues. Besides, the system reduces the time and cost of Green IT practice implementation by capturing, retaining and reusing past knowledge for improved decisionmaking. Practically, the system provides decision support by providing best-practice recommendations to IT practitioners on Green IT nomenclature to be implemented in their industrial operations. |
format |
Article |
author |
Bokolo, Anthony Jnr Mazlina, Abdul Majid Awanis, Romli |
author_facet |
Bokolo, Anthony Jnr Mazlina, Abdul Majid Awanis, Romli |
author_sort |
Bokolo, Anthony Jnr |
title |
Heterogeneous agent-enabled decision system for evaluating Green IT performance in industrial environments |
title_short |
Heterogeneous agent-enabled decision system for evaluating Green IT performance in industrial environments |
title_full |
Heterogeneous agent-enabled decision system for evaluating Green IT performance in industrial environments |
title_fullStr |
Heterogeneous agent-enabled decision system for evaluating Green IT performance in industrial environments |
title_full_unstemmed |
Heterogeneous agent-enabled decision system for evaluating Green IT performance in industrial environments |
title_sort |
heterogeneous agent-enabled decision system for evaluating green it performance in industrial environments |
publisher |
Taylor & Francis |
publishDate |
2018 |
url |
http://umpir.ump.edu.my/id/eprint/21570/1/6.pdf http://umpir.ump.edu.my/id/eprint/21570/ https://doi.org/10.1080/12460125.2018.1490550 |
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