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Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

Due to greater returns to high skill and desirable amenities, high-skilled workers are increasingly agglomerating in metropolitan areas and form path dependence. This chapter explores whether the land supply policy of China constraining big cities' urban construction land quota strengthens the spatial divergence of human capital. Using city-level land supply data, population census data, and land transaction micro data, we find that the higher the degree of a city's land supply lagging behind land demand, the greater the enlargement effect of the initial share of population with college degrees on the increase in share of population with college degrees. Further research reveals that the main mechanism causing this phenomenon is the rapidly rising housing prices hindering low-skill labor flows to big cities.

This chapter aims to shed light on the role that a sustainable orientation plays in strengthening the relationships between global consumers and online brands. Despite many previous studies about the importance of sustainability considerations for national consumers’ brand commitments and purchase intentions, there is a lack of empirical studies focussing on this relationship from a global consumer perspective. A pre-study (consisting of focus group discussions) and a widely distributed international survey with responses from 74 countries show mixed results. Whereas the results from the focus groups imply that a sustainable orientation influences both global consumers’ purchase intentions and brand commitments towards online brands, the survey results imply that global consumers’ sustainable orientations do not affect purchase intentions directly, even though they influence brand commitments. An implication of these results is that an international online brand’s possibility to portray a sustainable orientation plays an important role in strengthening the relationship with global consumers, especially regarding brand commitment.

Greenhouse gas (GHG) emission has a detrimental impact on climate change. There is an increasing trend for firms to use disclosure to signal stakeholders about its environmental responsibilities and performance in dealing with climate change. China is one of the countries producing the most carbon emissions. Over the last decade, Chinese state-owned enterprises (SOEs) are becoming important players in international trade. However, the existing literature provides limited evidence on how Chinese SOEs influence GHG disclosure. Through the lens of stakeholder–agency theory, this chapter studies the top 300 listed firms to examine the relationship between Chinese SOEs and the likelihood of GHG disclosure. The result suggests a negative relationship between Chinese SOEs and the likelihood of GHG disclosure. This could be explained as a consequence of the managers' political self-interests, economic and policy-oriented decision-making process and the power differentials between the government and SOE managers. This research extends the GHG literature to Chinese SOEs context, providing direct evidence on how state ownership impacts on GHG disclosure.

Despite efforts to reduce environmental pollution and wasteful fossil fuel use, electric vehicles (EVs) are still rare on the road. Why is it so challenging to get widespread EV adoption? One significant factor on which it heavily depends is one's awareness and understanding of EVs. However, due to an absolute lack of knowledge on the part of the populace, this factor becomes a huge impediment to the uptake of EVs. A systematic review of the electronic database Scopus for the years 2003–2022 was carried out on ‘EV awareness and adoption of EV’ while considering the ‘Preferred Reporting Items for Systematic Reviews and Meta-analysis’ (PRISMA) standards. A three-step identification process resulted in the ultimate detection of 41 papers, which were then thoroughly examined. A conceptual framework that encompasses the three key awareness aspects that influence EV adoption is developed. To encourage greater uniformity among EV researchers, this study's conclusions serve as a foundation for operationalising upcoming research efforts within a predetermined framework. The authors must therefore be optimistic that lingering technological, legislative, cultural, behavioural and business-model barriers may be overcome over time through widespread dissemination of knowledge and awareness related to EVs, making it possible for everyone to switch to greener, more economical and more efficient transportation solutions.

Currently, waste is regarded as a symptom of inefficiency. The generation of waste is a human activity, not a natural one. Currently, landfilling and incinerating wastes are common waste management techniques; but the use of these methods, in addition to wasting raw materials, causes damage to the environment, water, soil, and air. In the new concept of “Zero Waste” (ZW), waste is considered a valuable resource. A vital component of the methodology includes creating and managing items and procedures that limit the waste volume and toxicity and preserve and recover all resources rather than burning or burying them. With ZW, the end of one product becomes the beginning of another, unlike a linear system where waste is generated from product consumption. A scientific treatment technique, resource recovery, and reverse logistics may enable the waste from one product to become raw material for another, regardless of whether it is municipal, industrial, agricultural, biomedical, construction, or demolition. This chapter discusses the concept of zero landfills and zero waste and related initiatives and ideas; it also looks at potential obstacles to put the ZW concept into reality. Several methods are presented to investigate and evaluate efficient resource utilization for maximum recycling efficiency, economic improvement through resource minimization, and mandatory refuse collection. One of the most practical and used approaches is the Life Cycle Assessment (LCA) approach, which is based on green engineering and the cradle-to-cradle principle; the LCA technique is used in most current research, allowing for a complete investigation of possible environmental repercussions. This approach considers the entire life cycle of a product, including the origin of raw materials, manufacturing, transportation, usage, and final disposal, or recycling. Using a life cycle perspective, all stakeholders (product designers, service providers, political and legislative agencies, and consumers) may make environmentally sound and long-term decisions.

Agency problems are more severe for multinational corporations (MNCs) and multinational enterprises compared to their domestic counterparts. As companies develop diversified operations, their managers face more challenges. An incentive compensation structure has been designed to align the benefits of managers with those of shareholders. Additionally, corporate social responsibility (CSR) has become increasingly crucial for companies. MNCs must gain the trust of more investors to improve their corporate reputation and financial performance. CSR enables MNCs with a high sense of social responsibility to expand their investor base, reduce perceived risks, and decrease information asymmetry. Our empirical findings reveal that Taiwanese MNCs can enhance their performance by implementing cash-based compensation and pursuing CSR activities.

Artificial Intelligence (AI) is one of the newest technology that is quickly advancing and can be utilised to improve human resource competence in the age of rapid digital transformation. The present competitive scenario demands accurate data that need to be collected and analysed for organisational growth.

Purpose: The research examines the applications and usage of AI in performance management and further analyses the future of PM from the perspectives of AI.

Methodology: The study is conceptual and relies on secondary data from research papers, publications, HR blogs, survey reports and other sources. Employee performance and attitudes were monitored using digital technologies, big data analytics and AI. The quality of employee performance continues to increase with the integration of AI, enabling predictive analytics to increase employee performance.

Research Implication: In employee performance appraisal, a digital performance management system leads to openness and honesty with time, effort and sincerity. It is based on the performance management system’s practical usefulness.

Theoretical Implication: The study’s findings provide HR managers, academics, IT professionals and practitioners with an understanding of how AI may be used for performance management and its consequences on their operations. In addition, the connection between the HR devolution theory on performance management and AI is discussed.