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By using experiential learning theory, this study aims to examine how students engage in sustainable living practices that can improve their sustainability literacy and behaviours. It also explores their motivations and enablers. In doing so, the research seeks to develop a curriculum model that may assist educators in designing learning activities for sustainable living.

A qualitative study is conducted with 38 second-year undergraduate students on a sustainability-related module. Students are asked to engage in sustainable living practices for a six-week period. Descriptive statistics and inductive/thematic analysis are carried out on students’ reflective reports.

The results reveal five top sustainable living practices for students. The use of technology is revealed as an important enabler. Sustainable living motivations and approaches, and new skills are revealed. A sustainable living curriculum model is developed as a student-centric approach for fostering sustainability values.

The findings have implications for those teaching sustainability on the design of their learning content and activities by taking a student-centric approach to sustainable living. It also encourages active reflection throughout using an incremental learning process.

The research contributes to the existing literature by showing different choices and approaches for students’ sustainable living that can be considered when designing curriculum and educational activities to encourage maximum interaction in sustainable living. It develops a new curriculum model specific to sustainable living, and also builds on the concept of “learning by living”, an extension of learning by doing.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

Although much research has examined sustainable consumption, one key factor that has been rediscovered is religion. This study aims to include religiosity as a background variable to extend the theory of planned behavior in measuring the Pakistani youth’s green purchase intentions (GPI) and green purchase behavior (GPB) of energy-efficient home appliances.

Built on a positivist research philosophy and a deductive approach of a quantitative design, a convenience sample of 317 participants was approached via online forms. Partial least squares structural equation modeling was used to analyze both the measurement model and the structural model.

The results suggest that religiosity impacts consumers’ beliefs to maintain control over green behavior and perceived behavioral control (PBC), followed by sustainable attitudes (SA), beliefs that significant others endorse green behavior subjective norms (SN) and GPI. Besides, PBC, SN and SA impact GPI. Furthermore, GPI and PBC impact GPB. Finally, PBC, SN and SA mediate the religiosity and GPI link. However, the moderation effect of PBC on the link of GPI with GPB was not supported.

The model developed is specific to the Muslim population in Pakistan. Therefore, the model might only be able to be generalized to nations that have a similar culture to the Muslims in Pakistan or in other developing countries.

The current research advances the knowledge on the 2030 Agenda for sustainable development goal (SDGs) (Goal-12) by clarifying the mechanisms whereby religiosity impacts factors of sustainable consumption including SA, PBC and SN.

The purpose of this study is to assess the validity of the psychological safety (PS), psychological empowerment (PE), intrapreneurial behaviour (IB) and individual performance (IP) construct measurements originally developed in Western individualistic cultures.

Proportionate stratified systematic sampling was used among the production/operations middle managers in Nigerian medium enterprises (MEs), resulting in 355 valid responses. The measurements were analysed through internal consistency analysis, content, convergent and discriminant validity analysis.

The result shows that all four construct measurements are suitable and appropriate to gauge the respective constructs in collectivistic cultures such as Nigeria.

Cross-sectional self-reported data were used to analyse the result of this study, which may lead to common method variance.

Organizations, especially MEs, can use the validated measurements of this study to enhance work results in the Nigerian context.

Collectivistic cultures can benefit from the widely used measurements of PS, PE, IB and IP despite been originally developed in Western individualistic cultures.

This paper extends the body of knowledge by validating the measurements of PS, PE, IB and IP in collectivistic cultures such as Nigeria. Measurement validation for these constructs is scarce in this context. Thus, this study will provide a consistent and efficient reference for forthcoming studies and improve the credibility and replicability of future research results in collectivistic cultures.

The purpose of this study is to examine the dimensions of organizational learning (OL), entrepreneurial orientation (EO), personal value toward the firm performance of small and medium enterprises (SMEs) in North Sumatera, Indonesia.

This study used a quantitative methodology using Smart partial least squares of the structural equation model. A survey is done by distributing the questionnaires to the respondents (owner-managers) of SMEs across sectors. Using a convenient sampling technique, 128 respondents are selected. Using a cross-sectional survey design, 11 hypotheses are tested.

It is found that the innovativeness of EO and personal value both have a significant relationship with firm growth. While OL is significantly related to the innovativeness of EO, risk-taking of EO and proactiveness of EO. Then, both innovativeness of EO and proactiveness of EO significantly mediate the relationship of OL and firm growth. However, OL, proactiveness of EO and risk-taking of EO are insignificantly related to firm growth, while risk-taking of EO also insignificantly mediates the relationship of OL and firm growth.

EO (innovativeness, risk-taking and proactiveness) is deemed a crucial factor in running businesses by SMEs, while OL and personal value play a significant role in creating a competitive advantage that is needed for growth.

Despite the growing interest in closed-loop manufacturing, there is a lack of comprehensive frameworks that integrate product development, production processes, people and policies (4Ps) to optimize sustainable manufacturing performance. This study investigates the influence of the four Ps of closed-loop manufacturing systems (product development, production processes, people and policies) on sustainable manufacturing performance (SMP).

To investigate the influence of the four Ps on SMP, a hybrid analytical model was employed, combining structural equation modeling (SEM) with artificial neural networks (ANN). Data were collected through a structured survey administered to 353 manufacturing firms in Malaysia. SEM was used to assess the relationships between the variables, while ANN was employed to capture nonlinear relationships and improve prediction accuracy.

The research findings demonstrate that product development practices, including eco-design, life cycle assessment and resource planning, exert the most significant influence on SMP. Furthermore, implementing green and lean manufacturing techniques, energy modeling and material utilization/toxicity planning significantly enhances sustainability outcomes. While the social setting (employee motivation, turnover and work–life quality) does not directly impact SMP, it plays a pivotal role in facilitating the implementation of internal environmental policies. Moreover, environmental management practices, both mandatory and voluntary, serve as intermediaries between the four Ps and SMP within closed-loop manufacturing systems.

The findings offer valuable insights for policymakers, industry leaders and manufacturing organizations. By prioritizing product development, implementing green and lean manufacturing practices and fostering a positive social setting, organizations can significantly enhance their sustainable performance. Additionally, the study highlights the importance of effective environmental management practices in mediating the relationship between other factors and SMP.

This study contributes to the literature by providing a comprehensive framework for understanding the factors that drive sustainable manufacturing performance. The hybrid SEM-ANN model offers a robust and innovative approach to analyzing the complex relationships between the four Ps and SMP.

This paper aims to identify current challenges that hinder university–industry (U-I) collaboration in Pakistan and presents future opportunities for promoting such collaborations in developing countries.

This exploratory study presents new empirical evidence obtained from Pakistan via a questionnaire survey of 24 universities, 25 interviews with key stakeholders including industry managers and outputs from a high level workshop event.

Although there is limited evidence of U-I engagement in Pakistan, the findings show that a lack of coordination between government, universities and industrial firms has hindered knowledge transfer between universities and industry. Such steps as utilising intermediaries to help broker effective collaborations and building trust-based relationships can help in socialising these types of scientific activities.

Any overall conclusions drawn from this exploratory study can only be tentative, as the findings represent a snapshot of current U-I collaboration initiatives in Pakistan.

Less stringent policy interventions from government entities, as well as more universities willing to invite industry input on their board of studies might enable co-development of some university curriculums with industry partners. U-I collaborations could also help to boost innovation efforts in developing country firms.

This paper also offers awareness into benefits of teaching activity collaboration with industry partners, which has been an under explored area of past U-I collaboration studies. The findings should be of interest for both innovation policy and higher education policy researchers.

This study aims to explore the synergetic effects of total quality management and supply chain management (TQM–SCM) initiatives and their effects on organizational performance (OP). This research has been conducted in Pakistan’s logistics sector. The research reveals the synergistic effect of TQM and SCM initiatives and their effects on OP.

The constructs of the TQM and SCM were chosen after reviewing the literature that was critical for the logistics sector. The synergetic effect of TQM–SCM on OP has been evaluated. The mediating, direct and indirect effects were also evaluated in different models independently. Structural equation modelling was applied to drive the results via using AMOS.

It was observed during the analysis that both the TQM and SCM have a significant effect on OP. Both TQM initiatives have directly correlated to the improvement in SCM, and both have a positive effect on an organization. This research study has aided logistics firms that are focusing on TQM and SCM planning and implementation. The results can give management a better and more in-depth knowledge of the TQM initiatives and OP.

The data was collected through email and personal visits from different organizations. The data was collected through an adopted questionnaire. It is found in the study that many people at the managerial level have limited knowledge regarding SCM and TQM. The results may vary if the knowledge of the employees is improved.

The current study presents an upscale addition by examining the function of SCM and TQM linkage in OP as well as their relationship. The evaluated model serves as a guideline for firms looking to expand and achieve maximal OP.

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The evaluated model is developed in this study that serves as a guideline for firms looking to expand a new method to reach maximum OP.

The purpose of this study is to examine the moderating influence of the external environment on the relationship between entrepreneurial competencies, entrepreneurial orientation, entrepreneurial network, government business support and SMEs performance. The objectives of the study are achieved using the resource-based view and dynamic capability theory.

The survey method of research was used by personally administering questionnaires to the respondents. Multistage sampling techniques are used in selecting 470 SMEs owners/managers that participated in the survey. SPSS 24 and PLS-SEM 3.0 were used in the analysis of the data.

In the Nigerian context, the findings indicated that EC, EO and GBS directly influence the SMEs performance. Surprisingly, SMEs performance is not influenced by EN. Similarly, EE significantly moderated the relationship between EC, GBS and SMEs performance. On the contrary, EE does not have any moderating influence on the relationship between EO, EN and SMEs performance.

The study is limited to northeastern Nigeria. The study is limited to the EC, EO, EN GBS EE and SMEs performance and the use of cross-sectional data. The findings imply that SMEs owners/managers need a high level of entrepreneurial competencies and government business support to achieve a better performance especially in an external environment that is characterised by dynamism, diversity, complexity and hostility. Hence, providing support for both RBV and DCT.

Thus, the study offers additional empirical evidence from Nigeria and also expands knowledge and understanding in this field. The findings offer owners/managers, government agencies, financial institutions and other stakeholders of SMEs strategies EC, EO, GBS and EE to achieve a better SMEs performance.

The conceptual framework of the study is unique, and the study was conducted in northeastern Nigeria which is grossly underrepresented in the literature. It also provided understanding on the moderating influence of EE on the framework.

This study aims to investigate the mediating role of different types of intellectual capital (human, structural and relational) in the relationship between artificial intelligence-driven supply chain analytics capability (AI-SCAC) and various supply chain decision-making processes, specifically rational, bounded and tacit decision-making.

The study used a quantitative survey strategy to collect the data. A total of 320 valid questionnaires were received from manufacturing companies. The data were analysed using structural equation modeling with partial least squares (PLS-SEM) approach through SmartPLS software.

The results indicate that human and structural capital significantly mediate the relationship between AI-SCAC and rational and bounded decision-making processes. However, structural capital does not mediate the relationship between AI-SCAC and the tacit decision-making process. Moreover, relational capital does not show a significant mediating effect on all of the decision-making processes. Notably, structural capital has the strongest impact on rational and bounded decision-making, while human capital plays a critical role across all three decision-making processes, including tacit decision-making.

This study contributes to the literature by providing a nuanced understanding of the differentiated impact of intellectual capital components on various decision-making processes within the context of AI-SCAC. While previous studies have broadly acknowledged the role of intellectual capital in decision-making, this research provides more understanding of how specific types of intellectual capital interact with AI to influence distinct decision-making processes. Notably, the differential impact of structural capital on rational and bounded decision-making versus tacit decision-making highlights the need for organisations to adopt a more tailored approach in leveraging their intellectual capital.