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The purpose of this paper is to develop a collaborative agent-based web architecture and an agent-based green IS assessment tool to aid information technology (IT) practitioners in data centers assess their current green information systems (IS) practice toward attaining sustainability.

The methodology comprises that the collaborative agent-based web architecture, agents’ algorithm and the green IS assessment tool, which is validated by employing focus group questionnaire targeting IT practitioners in seven Malaysian-based enterprises that have an in-house data centers. With 105 valid samples at hand, descriptive analysis and exploratory factor analysis was utilized to determine the applicability of the implemented agent-based green IS assessment tool.

Findings reveal that the agent-based green IS assessment tool possesses the capability to evaluate benchmark and rate enterprise data centers current green IS practice. Additional findings indicate that the agent-based green IS assessment tool provide suggestions on how green IS practice can be improved in enterprise data centers.

This study only collected data from 105 IT practitioners in enterprise data centers based in Malaysia; as such results from this research cannot be generalized to other countries. Moreover, the developed collaborative agents for green IS practice assessment can only be fully deployed after domain experts has added green IS practice assessment questions and alternative answers.

This study presents an autonomous agent-based green IS assessment tool that supports the assessment of enterprise toward inclusion of sustainability considerations to enhance enterprise environmental performance.

This study provides empirical evidence for data centers efficacy leading toward a greener society for environmental conservation for future generations to come.

This study creates awareness by presenting the green IS practice to be implemented by IT practitioners in data centers. In addition, the agent-based green IS assessment tool provides a web-based platform for promoting environmental sustainability by supporting data centers toward evaluating, benchmarking and rating their current green IS practices.

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 environmental responsibility.

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.

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.

The sample population in this study comprises only practitioners from educational institutions in Malaysia. Theoretically, this research provides feasibility factors and associated items that can be used in evaluating developed information systems.

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 green growth.

This study presents how case-oriented agents aid educational institutions in going green for environmental responsibility. Socially, this research provides the strategies for green practice improvement in educational institutions toward environmental responsibility.

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. Lastly, the statistical tests adopted in this paper can be used to gauge the feasibility of information system application in future.

This paper aims to investigate the current value chain activities grounded on Porter’s value chain theory and to examine the drivers of strategic environmentalism that influence sustainable value chain adoption. This study further constructs a prescriptive model to reveal the extent to which information communication technology (ICT)-based industries are adopting sustainable value chain practices.

Data were collected using questionnaire from selected ISO 14000/14001-certified ICT-based firms in Malaysia and analyzed using partial least square-structural equation modeling.

Results reveal that the primary activities positively influence sustainable value chain. Moreover, results indicate that support activities significantly influence sustainable value chain adoption in ICT-based firms. Results further show that strategic environmentalism drivers have an impact on sustainable value chain adoption.

Data were collected from ICT-based industries in Malaysia only. Additionally, this research extends the body of knowledge and offers theoretical implications for ICT-based industries in Malaysia and other emerging economies in adopting sustainable value chain activities.

Practically, this study assists ICT-based industries to change their current paradigm from the traditional operations to a more holistic approach toward supporting practitioners to simultaneously achieve social responsibility, environmental and economic growth.

This study offers social implications for ICT-based industries to implement cleaner operations by decreasing CO₂ emission, lessening energy usage, diminishing cost incurred and minimizing usage of natural resources, thereby increasing product recovery and recycle-ability of IT hardware.

This study is one of the first to address the issue related to sustainable value chain in ICT-based industry by providing a roadmap on how practitioners can implement sustainable initiatives or more significantly, how to infuse these initiatives in their current chain, while concurrently enhancing competitiveness. Furthermore, this paper examines the current activities implemented by practitioners toward sustainable value chain adoption and explores the correlation of the drivers of strategic environmentalism with regard to sustainable value chain.

The research study aims to investigate green supply chain management (GSCM) elements as part of a complete system. It aims to understand the special properties of the GSCM system under the moderating effects of product complexity and purchasing structure.

A thorough literature review led to the building of the conceptual framework. Six constructs were identified using systems theory. These constructs include green supply chain technological dimensions (particularly, Artificial Intelligence (AI) based), green supply chain strategy, green supply chain process, product complexity, purchasing structure, and firm performance. The instrument was scientifically developed for gathering survey responses using complete design test methods. The conceptual model was eventually tested based on survey data collected from 250 automotive components and allied manufacturers in the emerging economy of South Africa.

The results indicate that GSCM technological dimensions (AI-based) positively influence GSCM strategy. Further, GSCM strategy was found to positively influence the GSCM process. The GSCM processes have significant effects on environmental performance, social performance, and financial performance. The product complexity has a significant moderation effect on the paths GSCM strategy and GSCM process.

The findings from multivariate data analysis provide a better understanding of GSCM system dynamics and are helpful to key decision-makers. This unique model has elevated GSCM theory to a new level. There are limited studies available in the existing GSCM literature using systems theory. This study will offer an advanced/comprehensive understanding to readers in this relatively new concept.

The aim of this study is to develop a model grounded by the institutional theory to investigate blended learning (BL) implementation among faculty members in higher education and further validate the model.

Quantitative methodology was employed, and data were gathered through questionnaires among 188 e-learning directors, managers and coordinators at faculty/department in institutions, which implement BL.

Findings reveal that BL implementation by faculty members is significantly influenced by coercive, normative and mimetic pressures. Findings from this study also identified institutional initiatives that influence BL implementation. Accordingly, findings from this study provide insights into the institutional theory perspective toward BL. The findings support higher education to plan and initiate BL policies.

Data were collected from faculty members in universities, colleges and polytechnics only. Besides, this research is one of the limited studies that explore BL deployment from the lens of faculty members.

This research contributes to the existing literature on the institutional theory and BL by presenting significant initiatives as practical suggestions for educationalist and policymakers. Therefore, this study provides practical implications to better understand BL initiatives by providing insights into how institutions can improve faculty members' satisfaction levels, improving course management, enriching teaching quality and enhancing learning content.

The findings provided in this study can be employed to design practices, policies and a culture that support continuance use of BL systems among faculty members to achieve an effective institutional outcome.

This study contributes to existing BL adoption and develops a model to examine faculty member implementation of BL approach. This research has several suggestions for higher education in terms of practice to support adoption of BL. The developed model can also be employed by academics, administration and institutions to determine success initiatives for achieving an appropriate change in adopting BL in their institutions.

This study aims to develop a software agent-knowledge procurement management tool to address uncertainties from external and internal environments, such as record failure, slow logistics auditing and distribution delay toward improving procurement management in retailing enterprises.

Quantitative methodology was used to collect data using a self-administered survey from randomly selected procurement staffs, marketers and customers to measure their perception regarding the feasibility and acceptance of the implemented agent-knowledge-based procurement management tool.

Results from empirical analysis reveal that the implemented tool facilitates collaboration and interaction among buyers, sellers and procurement managers toward enhancing procurement managers’ flexibility to handle unexpected exceptions. In addition, results confirm the feasibility of the implemented tool in supporting procurement management toward handling inventory failure exception, which occurs in traditional procurement approaches. Moreover, descriptive results from user acceptance test verify that the tool was accepted by the respondents.

The limitation of this study is that the implemented tool is evaluated using data collected from respondents in Malaysia retailing enterprise only; thus, the results cannot be generalized to other enterprises and country. In addition, research implications from this study design a methodological and comprehensive software agent-knowledge-based model that support buyers, sellers and procurement managers with information to facilitate buying and selling operations.

Practically, the designed software agent-knowledge-based model describes how software agents collaborate with each other to facilitate procurement tasks and also use the knowledge base in the implemented tool to provide information sharing platform that manages the dynamics of procurement operations.

This research integrates software agents which are autonomous programs that carryout pre-defined task on behalf of end users. Socially, this study would be useful for procurement managers in developing mechanisms for instilling insights in retailing operations.

This research is among the first to attempt to develop a software agent-knowledge-based model to support procurement management in the retailing enterprise domain. It contributes to promote e-procurement practices by implementing a software agent-knowledge-oriented tool to address uncertainties experienced in retailing enterprise. It is envisaged that this study will provide basis for future research into e-procurement practices for retailing businesses in Malaysia and beyond.

Blended learning (BL) has been increasing in popularity and demand and has developed as a common practice in institutions of higher learning. Therefore, this study develops a model to evaluate the critical predictors that determine students' acceptance and deployment of BL in institutions of higher education based on the theory of planned behavior (TPB).

The empirical analysis entails data collected from 1,811 responses from an online survey questionnaire from students in Malaysian universities, colleges and polytechnics. Partial least square–structural equation modeling (PLS–SEM) was employed for data analysis.

The results reveal that the attitude, subjective norm, perceived behavioral control and self-efficacy were found to influence students' intention to accept BL. Moreover, results suggest that the intention of students to accept BL approach is significantly influenced by actual BL deployment.

Data were collected from students in universities, colleges and polytechnics only. Besides, this research is one of the limited studies that explored BL deployment in a Malaysian perspective.

Findings from this research not only add scientific evidence to BL literature but also provide a better understanding of the predictors that may motivate or discourage learners to deploy BL in institutions of higher learning.

Respectively, findings from this study aid students to acquire and apply knowledge on how to effectively improve BL initiatives in learning activities.

This study is one of the fewer studies that investigate students' behavioral intentions toward BL deployment in Malaysia. Additionally, this study contributes to the understanding of the predictors that influence students' intention to accept and deploy BL in their respective institutions.

This study aims to analyze the socio-ecological policy trade-off caused by technological innovations in the post-COVID-19 era. The study outcomes are utilized to design a comprehensive policy framework for attaining sustainable development goals (SDGs).

Study is done for 100 countries over 1991–2019. Second-generation estimation method is used. Innovation is measured by total factor productivity, environmental quality is measured by carbon dioxide (CO₂) emissions and social dimension is captured by unemployment.

Innovation–CO₂ emissions association is found to be inverted U-shaped and innovation–unemployment association is found to be U-shaped.

The study outcomes show the conflicting impact of technological innovation leading to policy trade-off. This dual impact of innovation is considered during policy recommendation.

The policy framework recommended in the study shows a way to address the objectives of SDG 8, 9 and 13 during post-COVID-19 period.

Policy recommendations in the study show a way to internalize the negative social externality exerted by innovation.

This study contributes to the literature by considering the policy trade-off caused by innovation and recommending an SDG-oriented policy framework for the post-COVID-19 era.

The purpose of this paper is to empirically assess the impact of integrated lean and green practices on the sustainable (environmental, economic and social) performance of a hotel supply chain.

Literature review and previous exploratory studies were used to develop a hypothesized model that characterizes the integrated lean and green (LeGreen) impact on supply chain sustainability. A case study of a large sample of the UAE hotels is used to collect and analyze empirical data, validate the measurement model and test study hypotheses using structural equation modeling (SEM).

The results showed that three major lean techniques (Kaizen, quality and productive maintenance) and three green techniques (health and safety, waste disposal and green certifications) have substantial impact on the sustainable performance of hotel supply chains. Further results revealed that LeGreen impacts are complementary. Lean techniques have the highest impact on the economic performance of the hotel supply chain and the least impact on the environmental performance. Green practices, on the other hand, have opposite impacts.

Although the study findings may vary in different contexts, study methodology and measurement model can be adapted to assess the LeGreen impact on the sustainable performance of hotel supply chains, as well as other service industries such as banking and health care.

The proposed assessment model is expected to be of great value toward the effective implementation of LeGreen practices across hotel supply chains in the UAE and globally. The study findings also provide guidelines for practitioners within the hospitality sector to undertake the proposed model and to adapt it for assessing and enhancing sustainable performance in other sectors of the service industry.

There is a growing emphasis by practitioners and academics on measuring the impact of LeGreen on the sustainable performance of service supply chains. However, the assessment of LeGreen impacts within the context of a hotel supply chain remains unexplored with a scarcity of comprehensive assessment frameworks. This study aims to fulfill this gap in literature and provide directions for researchers to expand the proposed model and to further analyze the integrated lean-green impact on the sustainability of supply chains of hotels and the service industry.

Construction firms worldwide are increasingly taking pragmatic steps towards addressing environmental problems arising from their activities. Nonetheless, there is a paucity of studies focused on the nexus between green construction and environmental performance. Hence, this study aims to examine the linkages between green construction practice and environmental performance.

An extensive literature review was conducted to identify the relevant dimensions of green construction practice and indicators for measuring environmental performance. Variables collated were then subjected to pre-assessment and pre-testing processes. The pre-assessment was used as a preliminary content validation where experts assessed the various dimensions of green construction practice and indicators for measuring environmental performance proposed and determine if indeed the variables represent what the study set out to measure. Data were collected from construction professionals within the Ghana's Kumasi Metropolis. The sample size for the study was 100 experts in sustainable construction methods in the construction industry. A total of 63 responses were received out of the 100 target respondents, accounting for a 63% response rate. Data generated was analysed using mean score analysis and one-sample t-test to determine the level of significance of the various green construction practices and indicators for measuring environmental performance. A Pearson correlation analysis was undertaken to ascertain the relationships that exist among the various dimensions of green construction practice and indicators for measuring environmental performance. Finally, multiple linear regression analysis was utilised to ascertain the effect of the adoption of green construction practice on environmental performance.

The results indicate that all the green construction practices and the indicators of environmental performance identified from the literature were significant at p = 0.05. The study's findings revealed that energy management is the most significant construct of green construction practice followed by storm-water management. Furthermore, the analysis showed that the preservation of water is the most significant environmental performance indicator followed by sanitation. The regression model developed also explained that 75% of the variations in environmental performance are explained by green construction practice.

Notwithstanding the study's achievements, one major limitation the research faced was the relatively small sample size.

This study provides sufficient data for construction professionals to identify the various green construction practices that could enhance environmental performance. The study's results showed that environmental performance could be improved by adopting the key green construction practices identified in this study. Pragmatic directions are also provided to stakeholders in the construction industry to take a critical look at the environmental performance indicators that were significant.

This pioneering research attempts to investigate the linkages between green construction practice and environmental performance in Ghana. Key results provide a critical evidential influence of green construction on environmental performance and make a crucial contribution to the current body of knowledge.