Design and Development of an Eco-Innovation Management Information System to Accelerate Firms' Digital Transformation Strategy
It is vital for firms to measure, and, report on, the impact of eco-innovation towards their environmental performance. Additive Manufacturing is an eco-innovation that contributes towards reducing the environmental impact of manufacturing. However, there is a lack of practical tools for management...
| Main Authors: | Munodawafa, R.T., Johl, S.K. |
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| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.33255 / |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2022
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128339101&doi=10.1109%2fACCESS.2022.3163248&partnerID=40&md5=deff4ea3949dedcb9649a827e79fec11 http://eprints.utp.edu.my/33255/ |
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| Summary: |
It is vital for firms to measure, and, report on, the impact of eco-innovation towards their environmental performance. Additive Manufacturing is an eco-innovation that contributes towards reducing the environmental impact of manufacturing. However, there is a lack of practical tools for management to monitor and report on firms' eco-innovation implementation and performance. This paper presents a prototype Eco-innovation Management Information System (EiMIS), developed to enable a firm's management to systematically manage and report on eco-innovation performance. Using a top-down approach, the EiMIS is developed through utilizing the C# and SQL programming languages for the Graphical User Interface (GUI), Database Management System (DBMS) and other technologies to collect, store (into a relational database) and manage eco-innovation performance data. A 4-tier architecture enables the EiMIS to: store, view and retrieve or generate eco-innovation performance reports; and generally, manage firms' eco-innovation performance data. This developed prototype could, help introduce information system platforms that: assist firms to collect data that can model their additive manufacturing; ease firms' eco-innovation performance reporting; improve environmental data management capabilities; and complement firms' digital transformation strategy. © 2013 IEEE. |
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