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Knowledge management model for promoting green software development adoption among software practitioners


Tee, Mcxin (2018) Knowledge management model for promoting green software development adoption among software practitioners. Doctoral thesis, Universiti Putra Malaysia.


Over the years, use of computing and information technologies (IT) has brought a powerful change in our lives. Although computing and IT improves our daily lives but the technologies have also been contributing to environmental problems. Hence, computing and IT industry is legally, ethically and socially required to “green” their products, applications, services and activities. Environmental sustainability becomes an important issue in the world due to numerous initiatives have been supported by worldwide movement and media coverage. Literature about green software development (Green SD) is increasing since year 2010. However, level of environmental awareness in software development (SD) industry is still low in practice. Currently, there is lack of method in existing literature on promoting green practices (the Green SD knowledge) with the aim of spreading environmental awareness in SD industry. On the other hand, existing literature about knowledge management (KM) implementation in green and sustainable development of various industries has proved that knowledge is the main and valuable asset in order to succeed in achieving environmental sustainability. However, there is lack of research has outlined KM as solution towards managing and sharing of green knowledge efficiently in SD industry. Therefore, this study aims to promote Green SD adoption in SD industry, through exploring KM implementation as facilitation tool to manage and share Green SD knowledge among software practitioners. As a result, a model is proposed which concerns different extents: 1) motivational drivers that motivate software practitioners to adopt Green SD, 2) importance of various green practices in software development life cycle (SDLC), 3) KM in terms of KM process and KM technologies for managing and sharing Green SD knowledge, and 4) perceived outcomes of applying KM in promoting Green SD adoption. Quantitative questionnaire survey was carried out by randomly distributing questionnaire to software practitioners. Data collected was empirically analysed with structural equation modelling partial least squares (SEMPLS). Analysis shows that ethical motivational driver, KM technologies of artificial intelligence, content creation and management technologies, and e-learning system positively and significantly contribute to promote Green SD adoption through KM facilitation. Besides, the analysis result also proves that all the proposed perceived outcomes: cost-saving, effort-saving and time-saving are positive and significant perceived outcomes of applying KM as facilitation tool to promote Green SD adoption. Objectives of this research are achieved by introducing KM models to provide direction and suggestions to the SD industry in addressing environmental sustainability issues. Contribution of this study is presenting a new dimension of green knowledge perspective in SD field of study because this study is the first attempt in research field to fill in existing research gaps by introducing KM in Green SD discipline. While managing and sharing of Green SD knowledge becoming easier, it encourage continuous learning in green practices and develop common understanding on Green SD principle among software practitioners. Moreover, the Green SD knowledge sharing is not only limited to software practitioners, but also is significant in helping to promote understanding among stakeholder and their participation in decision making on environmental issues. So that, in future, the SD industry can help in sustaining computing resources. Major outcome of this study is KM Process-Green SD Implementation Model which will be valuable roadmap for inspiring software practitioners to acquire and share Green SD knowledge at the right time in order to develop greener software products and achieve environmental sustainability in the long run.

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Additional Metadata

Item Type: Thesis (Doctoral)
Subject: Green technology
Subject: Computer systems - Energy conservation
Call Number: FSKTM 2018 64
Chairman Supervisor: Prof. Rusli bin Abdullah, PhD
Divisions: Faculty of Computer Science and Information Technology
Depositing User: Ms. Nur Faseha Mohd Kadim
Date Deposited: 11 Feb 2020 01:44
Last Modified: 11 Feb 2020 01:44
URI: http://psasir.upm.edu.my/id/eprint/76954
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