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In the dynamic landscape of 2023, global challenges are amplified by escalating conflicts and the COVID-19 aftermath. Developing nations like Vietnam face a critical juncture, requiring diversified economies for enhanced livelihoods and poverty reduction. However, this growth necessitates increased energy consumption, potentially escalating carbon emissions. Green innovation (GI) emerges as a beacon of hope, offering products and services designed for a minimal carbon footprint. Beyond socio-economic advancement, GI aligns with sustainable development goals. This study aims to  examine the influence of knowledge management (KM) and digitalization (DG) on GI, particularly in sustainable competitive advantage.

Using structural equation modeling and drawing upon a survey administered to 301 Vietnamese enterprises.

The findings illuminate diverse underpinnings between green product and process innovation, unravel the intricate relationship between KM, DG and GI, and provide crucial insights for firms seeking sustainable competitive edges.

This multidimensional approach significantly enriches the understanding of these pivotal elements in contemporary business landscapes.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

The emerging economies of Asia have made remarkable economic progress over the past few decades, primarily driven by rapid structural transformation towards industrialization and manufacturing in particular. The share of informal manufacturing sector value added to GDP and of employment in the informal sector in total employment has increased considerably in these countries. Although this shift from agricultural to industrial/manufacturing may be seen as positive for the goals of poverty reduction, increased standard of living, formation of human capital, etc., its impact on the environment is often not free from contention. The aim of the paper is to examine the impact of informal manufacturing sector growth on environmental degradation in emerging Asian economies. Here, we have used CO₂ emissions as an indicator of environmental degradation. The impact of other exogenous variables, such as population growth, energy consumption, trade openness and foreign direct investment, has also been studied. We have employed the fixed effect model and the random effect model on the data spanning from 2000 to 2022. We have also used the Hausman test to check the suitability of the models. The results of the analysis indicate the presence of a U-shaped relationship between CO₂ emissions and informal manufacturing growth, thus refuting the validity of the Environmental Kuznets Curve hypothesis.

This study aims to deepen our understanding of how conventional technologies and robust accounting education standards can impact the effectiveness of green accounting practices in enhancing firm performance. To achieve this, the paper explores the moderating effects of artificial intelligence (AI) and accounting education quality on the relationship between green accounting and firm performance.

Using generalized method of moments estimation, this research uses a comprehensive dataset comprising 32,680 firm-year observations of listed companies from ten prominent countries – Canada, the UK, the USA, China, France, Germany, India, Japan, South Korea and Italy – over the period from 2012 to 2022. These countries, selected based on their high gross domestic product rankings as reported by the International Monetary Fund, ensure a diverse representation of economic strengths and capture a wide range of green accounting practices.

The study shows that green accounting practices positively impact current firm performance. Country-level AI positively moderates this relationship, suggesting that advanced AI infrastructure enhances the benefits of green accounting through improved data accuracy and decision-making. However, country-level accountancy education quality negatively moderates the relationship, indicating that stringent implementation of green accounting standards in these regions may introduce complexities and costs that reduce firm performance.

Integrating AI enhances data processing, predictive analytics and decision-making, improving green accounting effectiveness. High-quality accounting education ensures accurate reporting and greater transparency. These insights, when applied, can empower businesses to optimize sustainability strategies, assist policymakers in developing targeted regulations and guide educators in preparing accountants for the evolving demands of green accounting.

To the best of the authors’ knowledge, this study is the first to explore the combined moderating effects of AI and accounting education quality on the relationship between green accounting and firm performance. By highlighting the synergistic role of digital innovation and robust educational standards, this research offers novel insights into how these factors can enhance the effectiveness of green accounting practices and improve financial outcomes.

The field of medical technology is constantly evolving, leading to improvements in implantation techniques that offer innovative solutions for treating bone tissue defects. The purpose of this study is to investigate the integration of nano-silica into ceramic scaffolds to enhance the mechanical strength of Hydroxyapatite structures.

Using the design of experiment methodology, 13 distinct ceramic pastes, each optimized for specific mechanical characteristics, are formulated. Rheological testing is performed to ensure suitability for 3D printing, and the pastes are evaluated using techniques such as scanning electron microscopy and energy dispersive X-ray spectroscopy. The definitive screening design optimizer is used to determine an ideal material combination based on factors like extrudability, printability, strength and biocompatibility.

Scaffolds with the optimized HA/SiO₂ composition are fabricated and tested for compression strength, achieving 7.8 MPa.

The research endeavors detailed within this study represent a notable advancement in the augmentation of ceramic scaffold properties tailored for bone tissue engineering applications, particularly focusing on their suitability for integration within load-bearing structures. A particular emphasis is placed on the enhancement of printability, thereby facilitating streamlined fabrication processes.

Reducing CO₂ emissions from transportation is crucial for achieving carbon neutrality in the Gulf Cooperation Council (GCC) countries by 2060 or earlier. This study aimed at analyzing transportation-related energy consumption and CO₂ emissions, along with their determinants and mitigation measures planned to achieve carbon neutrality in GCC countries.

To achieve the study objectives, the pressure-state-response (PSR) framework was utilized. Various methods were employed within the PSR framework, including econometric analysis using EViews, energy modeling using the low emissions analysis platform (LEAP) and content analysis of relevant policy and national documents using NVivo.

The results indicated that population and economic growth, along with increased fuel consumption, have led to a growth in transportation-related energy use and CO₂ emissions in the GCC countries. Per capita transportation-related CO₂ emissions in the GCC countries are higher than those of several countries. To achieve carbon-neutral transportation, approximately 1.8 bn metric tons of CO₂ emissions need to be avoided by 2060 or earlier. Strategies related to fuel alternatives, vehicle technologies and mass transit have been planned to reduce transportation-related CO₂ emissions in the GCC countries.

This study employed a holistic approach to analyze transportation-related energy use and CO₂ emissions in the GCC countries. It provides several policy implications and highlights the urgent need for policy innovations to achieve transformative change in the transportation sectors of the GCC countries.

The paper follows Jason Cope's (2011) vision of a holistic perspective on the failure-based learning process. By analyzing the research since Cope's first attempt, which is often fragmentary in nature, and providing novel empirical insights, the paper aims to draw a new comprehensive picture of all five phases of entrepreneurial learning and their interplay.

The study features an interpretative phenomenological analysis of in-depth interviews with 18 failed entrepreneurs. Findings are presented and discussed in line with experiential learning theory and Cope's conceptual framework of five interrelated learning timeframes spanning from the descent into failure until re-emergence.

The study reveals different patterns of how entrepreneurs experience failure, ranging from abrupt to gradual descent paths, different management and coping behaviors, and varying learning effects depending on the new professional setting (entrepreneurial vs non-entrepreneurial). Analyzing the entrepreneurs' experiences throughout the process shows different paths and connections between individual phases. Findings indicate that the learning timeframes may overlap, appear in different orders, loop, or (partly) stay absent, indicating that the individual learning process is even more dynamic and heterogeneous than hitherto known.

The paper contributes to the field of entrepreneurial learning from failure, advancing Cope's seminal work on the learning process and -contents by providing novel empirical insights and discussing them in the light of recent scientific findings. Since entrepreneurial learning from failure is a complex and dynamic process, using a holistic lens in the analysis contributes to a better understanding of this phenomenon as an integrated whole.

The affordable loss (AL) heuristic, as one crucial sub-dimension of effectuation, delineates the maximum level of investment entrepreneurs are ready to lose in a worst-case scenario. Conflicting conceptualizations remain regarding whether entrepreneurs’ psychological traits matter for AL. Based on the narcissistic admiration and narcissistic rivalry perspective, this study investigates the relationship between chief executive officer (CEO) narcissism and AL behaviors.

Using data collected from the CEOs and paired vice presidents at 122 small and medium enterprises (SMEs) in mainland China, the authors intend to further explore the association between psychological traits, especially CEO narcissism and AL behaviors under environment and resource constraints (e.g. perceived uncertainty and slack resources).

The findings show that CEO admiration-based narcissism is positively related to AL behaviors in the firm. Furthermore, when firms hold more slack resources, narcissistic admiration has a stronger positive association with AL; while when the environment becomes more uncertain, narcissistic admiration has a weaker positive association with AL. In contrast, CEO rivalry-based narcissism is negatively related to AL behaviors in the firm. When the environment becomes more uncertain, narcissistic rivalry has a stronger negative association with AL.

This article contributes to trait-based effectuation research and suggests that individual psychological traits affect AL behaviors at the firm level, though the patterns of the relationship vary with both the type of narcissism and contexts.

As technology increasingly integrates into the restaurant industry, avatar servers present a promising avenue for promoting healthier dining habits. Grounded in the halo effect theory and social comparison theory, this study aims to delve into the influence of avatars' appearance, humor and persuasion on healthier choices and customer satisfaction.

This paper comprises three experimental studies. Study 1 manipulates avatar appearance (supermodel-looking vs normal-looking) to examine its effects on perceived attractiveness, warmth and relatability. These factors influence customer satisfaction and healthy food choices through the psychological mechanisms of social comparison and aspirational appeal. Studies 2 and 3 further refine this theoretical model by assessing the interplay of appearance with humor (presence vs absence) and persuasion (health-oriented vs beauty-oriented), respectively.

Results suggest that avatars resembling supermodels evoke stronger aspirational appeal and positive social comparison due to their attractiveness, thus bolstering healthier choices and customer satisfaction. Moreover, humor moderates the relationship between appearance and attractiveness, while persuasion moderates the effects of appearance on social comparison and aspirational appeal.

This research bridges the halo effect theory and social comparison theory, offering insights enriching the academic discourse on technology’s role in hospitality.

The findings provide actionable insights for managers, tech developers and health advocates.

Despite its significance, avatar design research in the hospitality sector has been overlooked. This study addresses this gap, offering a guideline for crafting attractive and persuasive avatars.

Despite a growing number of manufacturing firms actively collaborating with ecosystem members aiming for advanced service solutions, it remains unclear how digital collaboration capability (DCC) affects incremental service innovation (ISI) and radical service innovation (RSI) in the context of ecosystems. Drawing on dynamic capabilities theory and resource orchestration theory, this study aims to investigate the impacts of DCC on ISI/RSI and examine the mediating role of organizational agility (OA).

In this empirical paper, the authors obtained questionnaire data from 238 Chinese manufacturing firms embedded in the ecosystems. Then, the authors examined all the hypotheses through hierarchical regression analyses.

The empirical evidence indicates that DCC has a distinct effect on ISI and RSI. DCC positively affects ISI, whereas DCC shows an inverted U-shaped effect on RSI. In addition, OA mediates the positive effect of DCC on ISI within a certain range, whereas OA always mediates the inverted U-shaped effect of DCC on RSI.

This study enriches and extends existing research on DCC and service innovation by elucidating the heterogeneous effects of DCC on ISI/RSI and the complicated mediating role of OA. This study also has practical implications for manufacturing firms to revisit their collaboration capability and agility to boost ISI/RSI in the context of ecosystems.