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The chapter explains the Blockchain and its application in cryptocurrency and in various sectors. It gives an insight into the level of adoption of Blockchain technology globally based upon industry, country, and component. China is leading all nations worldwide, followed by the United States. The study will help to understand future research regarding its applications in different sectors of the economy. The study will also help to understand the significance and complications regarding risk and regulation. Its adoption in the logistics and supply chain is meant to achieve error-free communication and efficient tracking management.

As climate change impacts residential life, people typically use heating or cooling appliances to deal with varying outside temperatures, bringing extra electricity demand and living costs. Water is more cost-effective than electricity and could provide the same body utility, which may be an alternative choice to smooth electricity consumption fluctuation and provide living cost incentives. Therefore, this study aims to identify the substitute effect of water on the relationship between climate change and residential electricity consumption.

This study identifies the substitute effect of water and potential heterogeneity using panel data from 295 cities in China over the period 2004–2019. The quantile regression and the partially linear functional coefficient model in this study could reduce the risks of model misspecification and enable detailed identification of the substitution mechanism, which is in line with reality and precisely determines the heterogeneity at different consumption levels.

The results indicate that residential water consumption can weaken the impact of cooling demand on residential electricity consumption, especially in low-income regions. Moreover, residents exhibited adaptive asymmetric behaviors. As the electricity consumption level increased, the substitute effects gradually get strong. The substitute effects gradually strengthened when residential water consumption per capita exceeds 16.44 tons as the meeting of the basic life guarantee.

This study identifies the substitution role of water and heterogeneous behaviors in the residential sector in China. These findings augment the existing literature and could aid policymakers, investors and residents regarding climate issues, risk management and budget management.

Drawing on the socially embedded model of thriving and the idiosyncrasy credit model of leadership, this study aims to develop a moderated mediation model to investigate the roles that are thriving at work and leader competency play in the link between leader humility and creative service performance (CSP) of hospitality frontline service employees (FSEs).

To test the moderated mediation model, the authors applied a time-lagged research design and collected multi-source data from locally owned, star-rated hotels headquartered in the capital city of Pakistan. The authors collected the multi-source data at three different points in time from employees and their respective supervisors (N = 52 managers and their 312 immediate employees).

The results denote that leader humility positively impacts CSP, thriving at work mediates this impact and leader competency not only moderates the connection between leader humility and thriving at work but also magnifies the indirect association between leader humility and CSP via thriving at work.

The moderated mediation framework based on the socially embedded model of thriving and the idiosyncrasy credit model of leadership will benefit future researchers and practitioners while exploring the impact of leader humility (LH) on FSEs’ CSP in the hospitality context.

The fundamental contribution of this study is developing and testing a research model that concentrates on the effects of leader humility on FSEs’ CSP. Moreover, by receiving support on the mediating role of thriving, this research further sheds light on how subordinates under the leader with humility demonstrate high CSP. In addition, the moderating role of leader competency found in this study further highlights that leader effectiveness depends on the degree to which employees perceive their leader as competent.

Social presence (SP), which refers to individuals’ perception of others being engaged as “real people” in the same situation, is a crucial component in technology-rich learning environments (TREs). This study aims to identify major learning design, antecedents and outcomes of SP within TREs, and identify common findings from the past two decades.

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses review principles and a qualitative analysis of selected articles, a final review of 72 studies that met inclusion criteria was obtained. Key information, including education level, discipline, sample size, study type and measurements, was extracted and studies were further analyzed and synthesized based on design features and learning modes.

The study identifies five crucial factors for instructional design to foster SP in TREs: technology affordances, multimedia features, social factors, instructional principles, learner characteristics and learning management systems. The authors compare two learning modes across three dimensions and identify popular technologies used in studies related to SP over the past two decades. Practical recommendations are provided for educators and educational technology developers to enhance SP within technology-rich learning environments.

This research contributes to the discourse on online learning and computer-supported communication, particularly in the post-COVID-19 era. By examining factors influencing SP and providing implications for instruction and educational technology development, this study offers evidence-based support to educators for engaging learners and fostering authentic learning experiences through adaptive selection of educational technologies.

The purpose of this paper is to show that research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of policy formulation and implementation.

In view of the four dimensions which are internal demand, external pressure, policy innovation environment and service characteristic, a system of factors affecting policy diffusion is established. On this basis, a Multilayer Fuzzy Cognitive Map (MFCM) model for policy diffusion of GPPS is constructed. Nonlinear Hebbian Learning algorithm and genetic algorithm are applied to optimize the two components of the MFCM model, which are relationship between nodes at the same layer and influence weights between nodes at different layers, respectively. Taking Nanjing municipal government purchasing elderly-care services in China as the empirical object, simulation of policy diffusion based on the MFCM model is carried out, aiming to obtain the key factors influencing policy diffusion and the dynamic diffusion mechanism of GPPS policy.

Research results show that, compared with monolayer Fuzzy Cognitive Map, the MFCM model converges faster. In addition, simulation results of policy diffusion indicate that economic development level of jurisdiction, superior pressure, administrative level and operability of services are key influencing factors which are under four dimensions correspondingly. And the dynamic influencing mechanism of key factors has also been learned.

This paper constructs the MFCM model, which is a new approach based on several monolayer FCMs, to study the policy diffusion mechanism.

Utilising the resource dependency theory, this study investigates the impact of board interlocks (CEOs' interlocks, women board interlocks, independent board interlocks and total board interlocks) on carbon emissions performance in India.

This research applies varieties of regression methods comprising robust least squares, generalised method of moments and Heckman's regression on a final sample of 63 of India's top 200 Bombay Stock Exchange (BSE) listed companies that voluntarily participate in the Carbon Disclosure Project's (CDP) Climate Change Program and disclose their climate change data for years 2013–2020.

We provide strong evidence for a strong negative association between CEOs' interlocks and women board interlocks on carbon emissions performance. Independent and total board interlocks are not found to significantly affect carbon emissions performance.

Our sample is restricted to the proportion of the top 200 BSE firms that voluntarily submit their carbon emissions data to CDP. Also, the study's focus is India, limiting the generalisation of our findings to other emerging economies.

The study's findings provide valuable insight for regulators and corporate board of directors on the important role of CEOs and women board who interlock with other firms in steering the carbon emissions reduction. Specifically, the corporate board of directors should encourage CEOs to build more networks through outside board memberships. The regulators should revisit the Companies Act, 2013 and the Securities Exchange Board of India (SEBI) regulation to increase the number of multiple directorships of CEOs and women board of directors.

This study responds to the dearth of literature on the efficacy of board interlocks on carbon emissions performance in emerging economies.

The return behavior of customers has a great impact on the e-retail industry and has resulted in the emergence of return-freight insurance (RI). Additionally, customer loss aversion arising from returns affects e-retailers' decisions and manufacturers' profits. Therefore, the main purpose of the authors' study is to determine how e-retailers and manufacturers choose their RI strategy and pricing according to customers' loss aversion.

The authors propose three scenarios: no RI, customer purchase RI and free e-retail RI (FRI). Meanwhile, the authors also model a Stackelberg game between e-retailers and manufacturers for analysis. Then, according to customer return behavior and loss aversion, the authors study the optimal pricing decision and RI premium allocation scheme for e-retailers and manufacturers under different scenarios.

It was found that the loss sensitivity reduces customers' willingness to buy RI, which is not conducive to the development of e-retailers and manufacturers. Additionally, with higher loss sensitivity, e-retailers and manufacturers offer FRI to gain higher profits, which supports the implementation of the FRI strategy.

The authors introduce customers' loss aversion into RI to analyze the optimal pricing decisions and profits of e-retailers and manufacturers, enriching the application of loss aversion theory. In addition, this study analyzes the two-way cost-sharing mechanism between manufacturers and e-retailers to provide FRI, which provides a theoretical basis for RI premium sharing.

This paper aims at analysing the socio-economic characteristics, mobile phone ownership and banking behaviour as key determinants of digital financial inclusion in India.

This study is based on the Global Findex Survey of the World Bank covering 3,000 adult individuals in India. Simple statistical tools such as descriptive statistics, chi-square test and regression analysis with a marginal effect have been used for the data analysis.

About 35.2% of respondents have reported using digital financial services in the country. There is a significant association between the socio-economic profiles of individuals with the adoption of digital financial services in terms of gender, age, education, occupation and income. The marginal effect indicates that socio-economic factors, mobile phone ownership and banking behaviour of individuals towards borrowings and savings have indicated significant influence on digital financial inclusion. The analysis depicts that male with higher age, education, working status and higher income are more likely to adopt digital financial services. Further, individuals with mobile phone ownership and utilising banking in terms of borrowings and savings are more likely to adopt digital financial services.

As digital banking services have emerged as a preferred channel for financial service delivery, this study provides timely insights on developing user driven-strategies for promoting digital financial services.

Socio-economic characteristics, mobile phone ownership and banking behaviour are critical determinants of financial inclusion, so assessing its implications in the era of digitisation becomes imperative.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2022-0673.

The objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.

To accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.

In the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.

Employing the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.

This research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.