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Higher education has begun to attend to the importance of collaboration and self-awareness for educating sustainability leaders. However, there has been limited discussion on how to design a pedagogy that supports the development of these competencies, particularly the development of self-awareness. In this chapter, we introduce an experiential pedagogy in which students and faculty work together to develop self-awareness as the basis for sustainability leadership. We present three pedagogical principles that support the emotional learning that is foundational for sustainability leadership: student self-discovery, faculty as co-learners, and a developmentally focused learning environment. We demonstrate how these three principles work together to enable students and faculty to grow their self-awareness, providing the foundation for sustainable leadership. We conclude with a discussion on how management educators can learn from this case to develop sustainability leaders who have the self-awareness and relational competency to lead positive, inclusive organizations that are committed to sustainable business practices.

The study is aimed to compare the prediction success of basic machine learning and ensemble machine learning models and accordingly create novel prediction models by combining machine learning models to increase the prediction success in construction labor productivity prediction models.

Categorical and numerical data used in prediction models in many studies in the literature for the prediction of construction labor productivity were made ready for analysis by preprocessing. The Python programming language was used to develop machine learning models. As a result of many variation trials, the models were combined and the proposed novel voting and stacking meta-ensemble machine learning models were constituted. Finally, the models were compared to Target and Taylor diagram.

Meta-ensemble models have been developed for labor productivity prediction by combining machine learning models. Voting ensemble by combining et, gbm, xgboost, lightgbm, catboost and mlp models and stacking ensemble by combining et, gbm, xgboost, catboost and mlp models were created and finally the Et model as meta-learner was selected. Considering the prediction success, it has been determined that the voting and stacking meta-ensemble algorithms have higher prediction success than other machine learning algorithms. Model evaluation metrics, namely MAE, MSE, RMSE and R², were selected to measure the prediction success. For the voting meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0499, 0.0045, 0.0671 and 0.7886, respectively. For the stacking meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0469, 0.0043, 0.0658 and 0.7967, respectively.

The study shows the comparison between machine learning algorithms and created novel meta-ensemble machine learning algorithms to predict the labor productivity of construction formwork activity. The practitioners and project planners can use this model as reliable and accurate tool for predicting the labor productivity of construction formwork activity prior to construction planning.

The study provides insight into the application of ensemble machine learning algorithms in predicting construction labor productivity. Additionally, novel meta-ensemble algorithms have been used and proposed. Therefore, it is hoped that predicting the labor productivity of construction formwork activity with high accuracy will make a great contribution to construction project management.

Debates regarding climate change risk perception (CCRP), particularly its scale and impact on social and environmental sustainability, have continued for decades. CCRP is experiencing a renaissance with an increased focus on environmentally relevant behaviors to mitigate the effects of climate change. However, CCRP lacks investigation from the employee perspective. Supported by the social exchange and value–belief–norm theories, this study aims to address the impact of employees’ CCRP on their proenvironmental behavior (PEB) via the moderating roles of environmental values and psychological contract breach.

The nonprobability convenience sampling technique was used to collect survey data from a sample of 299 employees across 138 manufacturing firms in Pakistan.

The results show that employees’ CCRP positively impacts their PEB and that this relationship is moderated by their environmental values and psychological contract breach. Specifically, environmental values strengthen the CCRP–PEB relationship, while psychological contract breach weakens it.

The findings of the study emphasize useful guidance for managers and practitioners as a future avenue to restructure the climate change framework by emphasizing the conditions (i.e. environmental values and psychological contract breach). In doing so, the study is beneficial for managers and practitioners in helping to increase employees’ PEB through the development of climate change action plans.

To the best of the authors’ knowledge, this study is one of the first investigations into CCRP–employees’ PEB nexus in the developing country context. The study incorporates social exchange and value–belief–norm theory, which serve as the CCRP’s theoretical underpinnings. The findings advance the new knowledge about a firm’s social responsibility to achieve the sustainable development goals outlined in the UN’s 2030 Agenda.

The direction of causality between job satisfaction and job performance (known as the holy grail of industrial psychologists) is undetermined and related research findings in different organizational contexts are mixed. Based on the ample literature, mainly from Western countries, on the relationship between job satisfaction and job performance, a non-recursive bow pattern model was utilized to investigate the direct relationship between these two variables in an Asia–Pacific higher education system.

This study is quantitative in approach and survey in design. Additionally, to meet the statistical requirements of non-recursive bow pattern analysis, the authors added welfare as a theory-driven instrumental variable to introduce exogenous variability. Using the efficient partial least squares (PLSe2) estimator, the authors fitted the model to the data collected from 2008 academics affiliated with Malaysian public universities and polytechnics.

The results showed that while job satisfaction is considerably influenced by welfare, it is not a significant predictor of job performance directly. In addition, a meaningful positive correlation between the disturbance terms of job satisfaction and job performance was observed, suggesting the existence of other factors that could increase both job satisfaction and job performance. The findings' theoretical and practical implications are discussed, and a list of theory-driven evidenced-based policies in this regard is provided.

This is the first study to test a non-recursive bow pattern model and examine the holy grail of industrial psychology based on the PLSe2 methodology, as a parametric approach to partial least squares (PLS), in a higher education context. This study also provides higher education researchers with the advantages of the PLSe2 method, especially in causal-predictive modeling, in the context of applied higher education research.

The prevalence of crises is a real phenomenon that demands proper planning and implementation of measures to preempt and curb its consequences on both national economies and business operations. Crisis is one of the concepts that cannot be overlooked, pervasive in nature, and does not necessarily denote negativity. Crisis is no longer an unusual, arbitrary, or minor characteristic of today's business environment. As far as the business environment continues to be volatile and unpredictable, it is unlikely that business organizations would be free from crises. Crises are noted to be a vital part of a business context and can serve as an avenue for positive change and creativity if the right tools and techniques are employed to properly manage them. On the other hand, crises can jeopardize the continued existence of the organization and obstruct the achievement of its goals. Thus, the debilitating ramifications of crises on business growth, survival and overall success calls for adoption of sustainable crisis management approaches in this new business world order that is framed by Industry 5.0, digitalization, and green business practices. The primary purpose of this article is to establish how modern crisis management methods could lead to sustainable organizational development. The current study departs from existing studies in the literature by systematically presenting methods to anticipate, solve, and transform business crises into advantage. The chapter also throws light on how organizations should manage business crises that may well be accelerated by Industry 5.0 and its components; digitalization and sustainable development.

The purpose of this study is to get a clearer knowledge of the reasons for, approaches to and challenges associated with integrating sustainable development concerns into pipeline construction projects in New Zealand. To achieve this, this study delves deeply into sustainable construction to understand the reasons behind and incorporate sustainable development trials into their newly established product management and development procedure. As a result, this study looks at identifying key elements of sustainable construction practices and various interpretations of sustainability in the construction industry; offering a strategy for incorporating sustainable construction practices into the pipeline construction project in New Zealand; and benefits and difficulties that the construction industry encounters when implementing sustainable construction. Finally, a framework is developed to help in understanding the issues and potential solutions for integrating sustainable building methods into the pipeline construction project in New Zealand.

This study followed a four-step method (Figure 1), beginning with the identification of the data, continuing with the first screening of the data, determining eligibility and, finally, including the data. This data collection is being done to provide knowledge and direction for further research. Data were collected from various websites on the Web of Science and from Scopus databases. Additionally, data were gathered with the assistance of aggregator databases such as Scopus (scopus.com) and publishing databases such as Elsevier (sciencedirect.com), Inderscience, Taylor and Francis (tandfonline.com), Emerald Insight (emeraldinsight.com) and Google Scholar. These databases have been considered by a number of scholars to be reputable databases.

This research provided a thorough description of the key justifications for sustainable construction. This study demonstrated how the idea worked in practice by reviewing the literature on the relevance and analysis of sustainability in construction. This body of research identified crucial components of sustainable construction techniques and varied interpretations of sustainability in the construction industry. To better grasp the current application considerations in the construction sector, it also offered literature on sustainable construction methods. To determine the most effective strategy to make certain adjustments to the current construction processes, the literature also includes a wide range of sustainability-related topics in both developed and developing country contexts. This study also demonstrated the many perspectives and strategies for sustainable behaviors. Because the purpose of this study was to develop a strategy for implementing sustainable construction in New Zealand, it was of the utmost importance to shed light on the most well-known and prominent sustainable construction applications from across the world. The output of this aim provided the literature on construction practices to acquire insight into the ongoing conversations on sustainable practices and systems in the construction industry. This was done to obtain insight into the existing talks.

This research's contribution to the body of knowledge is demonstrated by the fact that this study has led to a better understanding of sustainable construction practices in the construction industry as well as the identification of the most significant challenges that businesses, organizations, educators and policymakers must face to improve their ability to put these strategies into practice. This research has provided a solid foundation for future research that aims to advance knowledge in this field by providing options for future research to evaluate the influence that the approach has had on enhancing the implementation of sustainable construction. Additionally, this study presents options for future research to evaluate the influence the approach has had on improving the implementation of sustainable construction. The successful completion of the research aim in the more traditional forms of higher education in the built environment can contribute to a better representation of new trends in the practice area associated with expanding and improving the construction industry sustainably.