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The main problem addressed by this research is the current debate between the negative and positive effects of industrial clusters. This debate is a result of gaps between theoretical implications and empirical evidence in both the classical agglomeration theory and the agglomeration lifecycle theory. The purpose of this study is to propose a framework for developing an index measuring both organizational cluster involvement and organizational supply chain including the three pillars (economic, social, and environmental). Furthermore, the index acts as a quantitative predictor of the stages of the life cycle of industrial clusters. Adopting a case study methodology, the applicability of the index development framework is demonstrated. First, cross-sectional exploratory interviews are performed to locate items measuring the three pillars of organizational sustainability within Egyptian communication industry. Second, an explanatory, cross-sectional approach is applied gathering data from eight professionals related to involvement and supply chain sustainability of their organizations. Analytical hierarchical process is used for weighting and aggregating individual item metrics into two indicators (Saaty, 1980). Measuring, managing, and controlling capabilities of organization's supply chains outweighs the need to manage risks. The proposed framework aids firms within a cluster in making timely decisions about what needs addressing to improve supply chain sustainability performance. Hence, all environmental, social, and economic capabilities can be effectively monitored and controlled.

This research focuses on the elements of pedagogy related to teacher–student engagement that promotes a responsive learning environment and improved outcomes for diverse populations in diverse contexts. We examine the pedagogical practices occasioned by the shift to online learning as a result of schools’ closures that followed the declaration of the global COVID-19 pandemic. Our analysis first explores the status of pedagogical practices and access to education technology following the implementation of the SDG4 agenda for an inclusive quality education for all. It follows with an exploration of pedagogical shifts in response to the pandemic following school closures, paying attention to the implications for equity for diverse populations in diverse learning contexts. The analysis draws from the education practice discourse surrounding the pandemic response gained from educators and students, gray literature, emerging scholarly publications, and institutional reports on the topic of pedagogical practices. Lessons from the experiences of the authors as researchers, students, and teachers illustrate examples of Zoom classroom practices that evolved with time that might support productive experiences for learners in technology-mediated learning environments. The global pandemic experience provides an opportunity for the field of comparative education to reconsider planning for the delivery of education in unpredictable and emerging emergencies.

The rapid advancement of Education Technology (EdTech) offers promising opportunities for educational institutions to integrate sustainable business practices into their operations and curriculum. The integration of EdTech into sustainability education has emerged as a powerful tool to promote environmental awareness, foster sustainable behavior, and address the pressing challenges of climate change and resource depletion. This chapter explores the growing significance of EdTech in sustainability education, analyzing its potential to cultivate a generation of environmentally conscious and responsible global citizens. It also aims at identifying and examining the most prominent emerging EdTech tools specifically designed to promote sustainability in educational settings. Furthermore, it aims to comprehend the institutional elements that have successfully incorporated and expanded the utilization of EdTech tools to promote enduring business practices. Additionally, the chapter addresses the challenges and obstacles faced by educational institutions in adopting and implementing these technologies and propose strategies to overcome these barriers.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

In this paper I investigate the nature of the differential in poverty by ethnicity in rural China using data from the Chinese Household Income Project in 2002. For that, I compare observed poverty with that in a counterfactual distribution in which ethnic minorities are given a set of relevant village and household characteristics of the Han majority. In particular, I investigate the importance of the location of minorities in explaining their higher poverty levels. The ethnic poverty differential does not change after equalizing the distribution of the population by geographical region (unless we use a higher poverty line). However, it is reduced after equalizing other locational characteristics of minorities (such as them living in less developed and mountainous areas), their larger number of children, their low education, and their fewer skilled non-agriculture workers. Finally, the ethnic per capita (log) income differential is shown to be higher for higher percentiles, with an increasing role of the geographical region as the main driver of these higher differentials.

This paper examines the impact of residents’ human capital investment inequality on the urban–rural income gap, using China’s provincial panel data from 1997 to 2013. The results show that, at the national level as well as at the regional level, residents’ overall human capital investment inequality has a positive significant impact on the urban–rural income gap. In addition, the impact of overall human capital investment inequality increased monotonically from the eastern region inward to the western region. In terms of the relative impact of each component of human capital investment inequality on the urban–rural income gap, migration investment inequality appears to have the greatest impact at the national level, whereas health investment inequality has the greatest impact on the urban–rural income gap in the eastern region, and education investment inequality exhibits the greatest impact in the central and western regions. We also investigate the impact of human capital investment inequality on the urban–rural income gap over different periods. The results show that residents’ overall human capital investment inequality had a positive impact on the urban–rural income gap in the period 1997–2008, but the impact rapidly shrunk in 2009–2013. Furthermore, the impact of residents’ health investment inequality on the urban–rural income gap shows a downward trend, and the impact of residents’ education investment inequality trended slightly upward from 1997 to 2008, and then rapidly shrunk in 2009–2013. Finally, the impact of residents’ migration investment inequality was only significant in 1997–2002.

Joon Y. Park is one of the pioneers in developing nonlinear cointegrating regression. Since his initial work with Phillips (Park & Phillips, 2001) in the area, the past two decades have witnessed a surge of interest in modeling nonlinear nonstationarity in macroeconomic and financial time series, including parametric, nonparametric and semiparametric specifications of such models. These developments have provided a framework of econometric estimation and inference for a wide class of nonlinear, nonstationary relationships. In honor of Joon Y. Park, this chapter contributes to this area by exploring nonparametric estimation of functional-coefficient cointegrating regression models where the structural equation errors are serially dependent and the regressor is endogenous. The self-normalized local kernel and local linear estimators are shown to be asymptotic normal and to be pivotal upon an estimation of co-variances. Our new results improve those of Cai et al. (2009) and open up inference by conventional nonparametric method to a wide class of potentially nonlinear cointegrated relations.

This chapter presents a theoretical framework of the industrial relations (IR) system in China’s coal mining industry, combining the roles of management organizations, workers, and trade unions, as well as government agencies. It is one of the first empirical attempts to investigate the relationship between human resource (HR) practices, labor relations, and occupational safety in China’s coal mining industry over the past 60 years, based on the secondary data on coal mining accidents and case studies of two state-owned coal mines in a northern city in Anhui Province, China. The fluctuating occupational safety has been affected by government regulations over different time spans, marked by key political agendas, and by coal mining firms taking concrete measures to respond to these regulations, while exhibiting differing safety performance in state-owned versus township-and-village-owned mines. The field studies compared a safety-oriented to a cost-control-oriented HR and labor relations system, and their influences on safety performance. Coal mining firms and practitioners are advised to shift the traditional personnel management paradigm to a modern HR management system. In addition, although workers are often blamed directly for accidents, it is suggested that workers’ participation and voice in various processes of decision-making and policy implementation, and trade unions’ active involvement in protecting workers from occupational hazards, be encouraged.

This chapter develops an asymptotic theory for a general transformation model with a time trend, stationary regressors, and unit root nonstationary regressors. This model extends that of Han (1987) to incorporate time trend and nonstationary regressors. When the transformation is specified as an identity function, the model reduces to the conventional cointegrating regression, possibly with a time trend and other stationary regressors, which has been studied in Phillips and Durlauf (1986) and Park and Phillips (1988, 1989). The limiting distributions of the extremum estimator of the transformation parameter and the plug-in estimators of other model parameters are found to critically depend upon the transformation function and the order of the time trend. Simulations demonstrate that the estimators perform well in finite samples.