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Purpose: Environmental, social, and governance (ESG) factors indeed play a vital role in sustainability efforts across various sectors and industries. ESG factors are often aligned with the United Nations’ Sustainable Development Goals (SDGs), which provide a framework for addressing global challenges related to poverty, inequality, climate change, environmental degradation, and more. Countries that prioritise ESG considerations in their operations and decision-making processes contribute to achieving the SDGs, thus advancing sustainability. The study explores the interplay between ESG practices and overall sustainability outcomes. This involves examining how ESG considerations influence environmental conservation, social equity, and economic resilience and how these factors collectively contribute to sustainability goals.

Methodology: Data envelopment analysis (DEA), which is performed in order to find out the most efficient countries, which will provide valuable insights into the complex relationship between ESG factors and sustainability, informing decision-making and driving positive change towards a more sustainable future.

Findings: ESG practices transform to sustainable development efficiently in half of the EU countries; however, the efficient countries differ depending on the model. Demonstrating the efficient transformation strengthens the country’s case for sustainability. Countries that embrace ESG practices not only contribute to environmental and social well-being but also enhance their competitiveness and long-term value-creation potential.

Implications: Policymakers can use the findings to advocate for policies and regulations that promote ESG integration and sustainable development. This may include measures to incentivise responsible business practices, enhance corporate transparency and disclosure, support sustainable finance initiatives, and strengthen regulatory frameworks to address emerging ESG risks.

This study aims to propose a cloud platform architecture considering information sharing based on blockchain to realize the security and convenience of enterprise information sharing in the automotive supply chain.

A bilateral matching model considering enterprises information contribution stimulates information sharing and improves the efficiency and quality of supply and demand matching. Three smart contracts are used to complete the information sharing process and match supply and demand in the automotive supply chain.

The system is tested on the local Ganache private chain, and the decentralized web page is designed based on the architecture prototype.

Solve the problem of information island in automobile supply chain.

This study aims to report the development and experimental evaluation of two kinds of PANI@semiconductor based photocathodic anti-corrosion coating, for application on stainless steel substrates.

PANI was in situ chemical polymerized on TiO₂ and BiVO₄ particles, and FT-IR and SEM/EDS were used to understand the characteristics and elemental distribution of the composite particles. Composite coatings, which consisted of epoxy, PANI@TiO₂ or PANI@BiVO₄ and graphene, were prepared on the 304L stainless steel. Photoelectrochemical response measurement, electrochemical tests and immersion tests were used to assess the anti-corrosion performance of the prepared coatings in 45°C 3.5 wt.% NaCl solution. And the corrosion protection mechanism was further explained by combining with surface observation.

The photoelectrochemical response tests revealed the good photocathodic effect of the coatings, and the reversible oxidation-reduction properties of PANI (pseudocapacitive effect) leading to the repeated usage of the coatings. Consequently, the anti-corrosion mechanism of the composite coating is attributed to the physical barrier effect of the coating, the anodic protection effect of PANI and the photocathodic and energy store effect.

These kind coatings could prevent corrosion from day to night for stainless steel, which has great engineering application prospects on stainless steel corrosion protection.

This study aims to holistically present a systematic literature review (SLR) triangulated with bibliometric analysis on environmental, social and governance (ESG) research to synthesize and comprehensively review its evolving journey and emerging research streams.

Using R-studio software, this study carried out a retrospective quantitative bibliometric analysis through performance analysis, science mapping and network analysis, covering 261 documents published on ESG research between 2007 and 2022 in Scopus and Web of Science databases.

Performance analysis depicts the trends in publications, impactful journals and influential publications, authors and countries, while science mapping incorporates co-words and thematic analysis. Likewise, co-occurrence analysis provided four different clusters, representing ESG research linkage to other management fields along with key insights from co-citation network analysis. Additionally, the theory–context–characteristics–methods (TCCM) framework has provided valuable results in terms of widely and emerging used theories, contexts, characteristics and methodologies in ESG research.

The findings of this study’s comprehensive bibliometric analysis combined with SLR uncovered a robust roadmap for further investigation in ESG research by identifying the inherent structure and evolution of research themes. This review has not only identified the prevalent gaps in determining priorities for future research but also provides insights which not previously been captured and evaluated on this topic.

To the best of the author's knowledge, no study presents the TCCM framework in the context of bibliometric analysis of ESG research. Besides, a conceptual framework is developed that illustrates antecedents, mediators, moderators and outcomes of research on ESG practices and provides the concluded key takeaways and recommendations for potential authors intending to publish their research papers on ESG practices.

As one of China’s most influential social platforms, Xiaohongshu is considered an underexploited market with significant user traffic. This study aims to build on existing scholarly work on social media marketing by conducting an empirical analysis of Xiaohongshu’s content to explore effective marketing strategies for children’s books.

This study uses qualitative content analysis to investigate the marketing practices for children’s books on Xiaohongshu. By systematically coding and interpreting data, the authors identified core marketing strategies and their interactions among publishers of children’s books on the platform.

Based on viral marketing and social proof theories, the analysis delineates practices and interrelations among three key marketing strategy components: content creation, traffic navigation and sales conversion on Xiaohongshu. From this analysis, a conceptual model titled “Continuous ‘Planting a Seed’ of Interest: Strategies for Marketing Children’s Books on Xiaohongshu” was developed.

This research not only corroborates the existing literature on the transformative power of social media in marketing but also extends it by providing a focused examination of how these principles apply to the promotion of children’s books on Xiaohongshu. It also provides practical insights for publishers looking to develop effective marketing strategies.

Compared to traditional (domestic) e-commerce consumers, cross-border electronic commerce (CBEC) consumers may face greater information asymmetry in the CBEC purchase process. Given this background, however, the literature has paid limited attention to the informational antecedents that influence consumers' perceptions of transaction costs and their CBEC purchase intentions. To fill this gap, this study integrates the elaboration likelihood model (ELM) and transaction cost theory (TCT) to develop a model for exploring how product (website informativeness, product diagnosticity and website interactivity as the central route) and external (country brand, website policy and vendor reputation as the peripheral route) informational antecedents affect consumers’ evaluations of transaction costs in terms of uncertainty and asset specificity and their CBEC purchase intentions.

This study employs a survey approach to validate the model with 766 Generation Z CBEC consumers based on judgment sampling. The partial least squares (PLS) technique is adopted for data analysis.

The results show that all the proposed central and peripheral informational antecedents reduce consumers’ perceptions of uncertainty and asset specificity, which in turn negatively influences their CBEC purchase intentions.

Through this investigation, this study increases our understanding of how product and external informational antecedents affect consumers’ evaluations of transaction costs, which subsequently determine their CBEC purchase decisions. This study offers theoretical contributions to existing CBEC research and has practical implications for CBEC organizations and managers.

A more accurate comprehension of data elements and the exploration of new laws governing contemporary data in both theoretical and practical domains constitute a significant research topic.

Based on the perspective of evolutionary economics, this paper re-examines economic history and existing literature to study the following: changes in the “connotation of production factors” in economics caused by the evolution of production factors; the economic paradoxes formed by data in the context of social production processes and business models, which traditional theoretical frameworks fail to solve; the disruptive innovation of classical theory of value by multiple theories of value determination and the conflicts between the data market monopoly as well as the resulting distribution of value and the real economic society. The research indicates that contemporary advancements in data have catalyzed transformative innovation within the field of economics.

The research indicates that contemporary advancements in data have catalyzed disruptive innovation in the field of economics.

This paper, grounded in academic research, identifies four novel issues arising from contemporary data that cannot be adequately addressed within the confines of the classical economic theoretical framework.

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.

The purpose of this paper is to analyze manufacturers' production decisions and governments' low-carbon policies in the context of influencer spillover effects.

This paper investigates the impact of the social influencer spillover effect on manufacturers' production decisions when they collaborate with intermediary platforms to sell products through marketplace or reseller modes. Game theory and static numerical comparison are used to analyze our models.

Firstly, under low-carbon policies, the spillover effect does not always benefit manufacturer profits and changes non-monotonically with an increasing spillover effect. Secondly, in cases where there are both a carbon emission constraint and a spillover effect present, if either the manufacturer or intermediary platform holds a strong position, then marketplace mode benefits manufacturer profits. Thirdly, regardless of business mode used when environmental damage coefficient is high for products; government should implement cap-and-trade regulation to optimize social welfare while reducing manufacturers’ carbon emissions.

This study offers theoretical and practical research support to assist manufacturers in optimizing production decisions for compliance with carbon emission limits, enhancing profits through the development of effective influencer marketing strategies, and providing strategies to mitigate carbon emissions and enhance social welfare while sustaining manufacturing activities.

This paper addresses the limitations of prior research by examining how the social influencer spillover effect influences manufacturers' business mode choices under government low-carbon policies and analyzing the social welfare of different carbon emission restrictions when such spillovers occur. Our findings provide valuable insights for manufacturers in selecting optimal marketing strategies and business modes and decision-makers in implementing effective regulations.

The purpose of this research is to develop a comprehensive model to better understand competitive dynamics between mobile payment providers in a multi-sided market featuring customers and merchants. This is undertaken by modeling customers performing financial transactions with merchants while two mobile payment systems (MPS) providers deploy different strategies to compete for market share.

The authors developed an agent-based simulation model using the NetLogo environment. The simulation featured two competing platform providers, 1,000 customer agents and 50 merchant agents. Past research, interviews and surveys were conducted to accurately model the behavior of the agents. Each simulation run lasted for 50 time periods. A total of 1,024 experimental conditions were designed to model different competitive environments, and 50 replications were conducted for a total of 51,200 experiments.

The simulation model provides insight into MPS platform providers’ competitive strategies by simultaneously modelling socioeconomic interactions between customers, merchants and MPS.

From a methodological perspective, the paper contributes a comprehensive model that can be used to study competitive dynamics between competing platforms in a multi-sided market. From the perspective of competitive strategies, the results show that pricing alone is not sufficient to influence MPS diffusion. Interactions between pricing, customers’ risk perception, perceived security and ease of use of the platform create unexpected same-side and cross-side network effects, which affect MPS diffusion.

While pricing remains a crucial lever for MPS to compete for market share, they should focus on enhancing customers’ and merchants’ trust and reduce their risk perception. This can be done through the improvement of the user experience of their platform, development of educational materials and marketing campaigns that address concerns around security, data breaches and perceived risk.

The paper is a direct response to a recent call for action on studying competition between MPS platforms by simultaneously modelling the socio-economic behavior of heterogeneous consumers and merchants. The proposed agent-based simulation model can be used to provide insights into competitive strategies and as a building block for subsequent research in this area.