Emerging case oriented agents for sustaining educational institutions going green towards environmental responsibility
| Pages | 186-214 |
| Date | 13 May 2019 |
| DOI | https://doi.org/10.1108/JSIT-10-2017-0083 |
| Published date | 13 May 2019 |
| Author | Bokolo Anthony Jnr.,Mazlina Abdul Majid,Awanis Romli |
| Subject Matter | Information & knowledge management |
Emerging case oriented agents for
sustaining educational institutions
going green towards
environmental responsibility
Bokolo Anthony Jnr.
Department of Computer Science, Norwegian University of Science and
Technology, NTNU, Trondheim, Norway, and
Mazlina Abdul Majid and Awanis Romli
Universiti Malaysia Pahang,
Faculty of Computer Systems and Software Engineering, Kuantan, Malaysia
Abstract
Purpose –The purpose of this paper is to design a system deployment model that integrates case-based
agent technique to develop an eco-responsibility decision support tool for greening educational institutions
toward environmentalresponsibility.
Design/methodology/approach –Data were collected through questionnaires distributed among a
statistical population that comprised practitioners across educational institutions in Malaysia that
implement green practices. The questionnaire measured the feasibility of the developed tool based on
factors derived from the literature. Accordingly, descriptive, exploratory and factor analysis approach
using statistical package for social sciences (SPSS) was used to test the feasibility of the developed
tool.
Findings –Results from descriptive analysis confirm the tool is feasible based on mean values that
range from 4.1619 to 3.6508 on a five-point scale, indicating that the tool is effective in sustaining
educational institutions going green. Besides, results from exploratory analysis verify the reliability
of the tool based on the acceptable Cronbach’s alpha reliability coefficient score higher than 0.7 and
Kaiser–Meyer–Olkin value being above 0.5. Finally, results from factor analysis reveal that the
developed tool is usable, efficient, helpful, flexible and credible and supports educational institutions
in going green at 88.44 per cent of the total variance, suggesting that the respondents are satisfied with
the tool.
Research limitations/implications –The sample population in this study comprises only
practitioners from educational institutions in Malaysia. Theoretically, this research provides feasibility
factors andassociated items that can be used in evaluating developedinformation systems.
Practical implications –Practically, this study develops an eco-responsibility decision support tool to
facilitate green strategies and provides information on how practitioners in educational institutions can
improve greengrowth.
Social implications –This study presents how case-orientedagents aid educational institutions in going
green for environmental responsibility. Socially, this research provides the strategies for green practice
improvementin educational institutions toward environmentalresponsibility.
Originality/value –The eco-responsibility decision support tool provides a Web-based platform for
promoting ecological protection by supporting the measuring of practitioners’current green practices for
environmental responsibility.Thus, research findings from this study are expected to help decision-makers
generate useful insights into environment-friendly strategies to be implemented in educational institutions.
JSIT
21,2
186
Received3 October 2017
Revised30 January 2018
21May 2018
23September 2018
Accepted9 May 2019
Journalof Systems and
InformationTechnology
Vol.21 No. 2, 2019
pp. 186-214
© Emerald Publishing Limited
1328-7265
DOI 10.1108/JSIT-10-2017-0083
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1328-7265.htm
Lastly, the statistical tests adoptedin this paper can be used to gauge the feasibility of information system
applicationin future.
Keywords Sustainability, Educational institutions, Environmental responsibility, Feasibility study,
Case-oriented agents, Green practice
Paper type Research paper
1. Introduction
Humanity is faced with several environmental issues, ranging from damage to the natural
environment and climate change to natural resources depiction (Nifa et al.,2015).
Accordingly, the number of users in educational institutions prompts for more sustainable
methods in the usage of information technology (IT) infrastructure deployed (Ramli et al.,
2014). Presently, owing to pressures from governmental and non-governmental
associations, educational institutions are motivated to implement green practices in their
institutional process, thereby supporting environmental responsibility (Ulkhaq et al.,2016).
Therefore, several approaches have been proposed, such as ISO 14000 framework and UI
Green Metric, which currently appraises and reports educational institutions in achieving
environmental sustainability(Sonetti et al.,2016).
Nevertheless, these approaches only serve as a guide to direct educational institutions
toward going green, but actually do not provide comprehensive information needed to
improve green practices (Anthony, 2016). Although ISO 14000 framework and UI Green
Metric (ISO, 2004a;UI Green Metric, 2016) do evaluate educational institutions’green
practices based on their in-house assessment procedures, they do not provide an
autonomous approach to measure educational institutions’green initiatives (Muladi and
Surendro, 2014;Hankel etal.,2016). Therefore, this study proposes two artificial intelligence
(AI) techniques that can be deployedto support educational institutions’green practicesfor
environmental responsibility.
Congruently, this researchintegrates agents to measure educational institutions’current
green practices andcase-based reasoning (CBR) to provide best practices supportto enhance
educational institutions’environmental responsibility. Respectively, an agent can be
considered as a pre-defined program that perceivesthe deployed environment using sensors
which helps to execute commands in the environment (Olsson and Funk, 2009). Likewise,
Wooldridge and Jennings (1995) define agents as a software or hardware system with
reactive, autonomous, pro-active and social abilities characteristics. An agent enables
flexible communications with other agents, humans and systems (Jnr et al., 2017b).
Similarly, CBR is one of the emerging techniques for deploying intelligent systems (Chang
et al.,2016). CBR addresses new problems by using previously successful solutions to
resolve similar problems(Jahani et al.,2015).
Currently, educational institutions are implementing green practices to promote
environmental responsibility toward attaining sustainability (Nifa et al., 2015). But at the
moment, there is need for tools to adequately provide up-to-date information on how green
practices can be implementedin educational institutions (Anthony et al.,2018). Furthermore,
practitioners in universitiesuse manual-based measurement of their current green practices.
Therefore, this article presents the green dimension or process to be implemented and
develops a system deployment model that integrates CBR and agents to develop an eco-
responsibility decision support tool that measures and provides information on how
educational institutionscan improve green practices strategies.
The structure of this paper is as follows: Section 2 presents the theoretical background;
Section 3 is the proposed system deployment model; Section 4 comprises results and
Sustaining
educational
institutions
187
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