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Migrant workers play a vital role in the development of countries such as China. However, they often face greater barriers in entrepreneurship. Yet, few studies have focused on the effect of institutional factors on migrant workers' entrepreneurial behaviors. To address this gap, this study concentrates on the role of taxation.

This study takes the agricultural tax abolition reform implemented in rural China since 2004 as an exogenous shock and uses the difference-in-difference (DID) method to examine its effect on migrant workers' entrepreneurship based on longitudinal data from the China Health and Nutrition Survey (CHNS).

We find that the reform significantly improves the probability of migrant workers engaging in entrepreneurship. Heterogeneity analysis reveals that the reform exerts a notably more pronounced positive impact on male, younger and migrant workers in the Western region. Further analysis reveals that the three main mechanisms are increased household income, female human capital accumulation and increased social capital, including social networks and social trust.

This study is first to offers an institutional perspective on the determinants of migrant workers' entrepreneurship in China. Additionally, the study can provide insights for policymaking intended to support employment and entrepreneurship among low-skill migrant workers.

By exploring the impact of digital knowledge resources (DKR) on the carbon emission intensity of the pig industry (PCEI), this study aims to reveal the role of DKR in reducing PCEI.

Based on provincial panel data in China from 2011 to 2021, this study uses the entropy and Intergovernmental Panel on Climate Change coefficient methods to calculate the evaluation index system of DKR and PCEI, respectively. Empirical analysis using a panel fixed-effects model examines the influence of DKR on PCEI and its underlying mechanisms.

DKR can significantly reduce PCEI. This conclusion still holds even after undergoing endogeneity treatment and a series of robustness tests. Mechanism test results indicate that DKR can operate indirectly through the mediation mechanism of rural human capital (RHC) and pig breeding technology innovation (PTI), while environmental regulation intensity (ERI) plays a positive moderating role in the relationship between DKR and PCEI. The magnitude of the impact of DKR on PCEI depends on ERI. Further studies found that the impact of DKR on PCEI has obvious heterogeneity characteristics, and the promotion effect is more obvious in regions with good integration degrees and high development potential.

This paper divides DKR into three dimensions: digital technology knowledge (DTK), digital management knowledge (DMK) and digital application knowledge (DAK), providing a new framework for research and enriching the understanding of the relationship between DKR and PCEI. Furthermore, the research results reveal the application potential of DKR in the pig industry, particularly in terms of resource allocation efficiency. This is of great significance for promoting low-carbon development in the pig industry and provides insights for the low-carbon transformation of other industries. In addition, the study emphasizes the moderating effect of ERI on the mechanism of carbon reduction in the pig industry through DKR. This offers a new perspective for understanding the relationship between knowledge management and environmental governance, providing a reference basis for policy formulation in related fields.

This paper further enriches the role of DKR in the livestock industry. Integrating DKR with traditional industries promotes knowledge innovation, information distribution and utilization and scientific decision-making. This has significant value in promoting the development and application of carbon reduction technologies, enhancing industrial competitive advantages, and other aspects.

The study aims to investigate the influence of stakeholder pressure on sustainability practices via the mediating effect of green innovation (GI) from a developing economy in Sub-Saharan Africa (SSA).

The study used primary data from 567 respondents in manufacturing and mining firms in Ghana to conduct the Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis using Smart-PLS, Version 4.0. Data was gathered using survey questionnaire. A purposive sampling method was used to choose participants' companies.

The findings revealed that shareholder and government pressure significantly and positively influence sustainability practices, while pressure from the community has an insignificant beneficial impact on sustainability practices. Consumer pressure revealed an insignificant detrimental influence on sustainability practices. The study discovered that green innovation fully and substantially mediates the association between stakeholder pressure and sustainability practices.

The study has limitations, including the exclusion of control variables and its focus on four different stakeholders, excluding other stakeholders that who also impact sustainability practices.

The study’s findings can assist Ghanaian companies in making strategic decisions to enhance corporate reputation, acknowledging the effect of stakeholder pressure on sustainability practices.

The study outcome may enable companies to implement more inclusive sustainable development initiatives, benefiting their bottom line while contributing to the well-being of local communities and the environment.

The study’s originality stems from integrating green innovation in examining stakeholders' influence and sustainability practices of firms, a gap that remained unexplored. It highlights the essence of green innovation in shaping a company’s sustainability practices, highlighting the need for businesses to integrate technology and sustainability in their operations.

This paper aims to analyze the role and advantages of knowledge resources in the carbon emission reduction of the industrial chain, and how it can be used to promote the carbon emission reduction of the industrial chain, so that the industry can better achieve the saving of energy and the reduction of emission.

This paper argues that the traditional resource-plundering industrial chain production method can no longer meet the needs of sustainable development of the green and low-carbon industrial chain, and builds the coupling and coordination of knowledge technology innovation drive and industrial chain carbon emission reduction mechanism, in the four dimensions of industrial chain organization, government support, internet support and staff brainstorming, put forward suggestions for knowledge resources to drive carbon emission reduction in the industrial chain.

This paper holds that the use of knowledge resource advantages can better help industrial chain enterprises to carry out technological innovation, knowledge resource digital platform construction, knowledge resource overflow and transfer, application and management of network information technology, so as to reduce carbon emission in industrial chain.

This paper contributes to the discussion about the high-quality implementation of the revitalization strategy of the industrial chain and also deepens research on the knowledge resource-driven carbon emission reduction of the industrial chain. Further, this paper enriches the role of knowledge resources in the industrial industry, and the theoretical results support the advantages of knowledge resource in the field of chain carbon emission reduction.

This study aims to provide supplements to the research on digital human avatar (DHA) and suggestions for brands to use DHA appropriately to build brand fans effect.

On the basis of integrating Avatar theory and Stimulus-organism-response theory, this study obtains data from 733 Chinese respondents aged 18–25 and uses regression analysis and bootstrap analysis to verify the relationships among the variables: DHA characteristics (form realism, behavioral realism and brand alignment) as the independent variables, brand fans effect as the dependent variable, consumer positive emotion as the mediating variable and product type (experience vs search) as the moderating variable.

The results show that DHA characteristics positively influence brand fans effect and consumer positive emotion, consumer positive emotion positively influences brand fans effect and consumer positive emotion plays a mediating role. Meanwhile, for experience products, the impact of DHA’s form realism and behavioral realism on consumer positive emotion is higher than that of brand alignment; for search products, the impact of DHA’s brand alignment on consumer positive emotion is higher than that of form realism and behavioral realism.

This study enriches and expands the empirical research perspectives and conclusions in the DHA field, improves its research framework and provides suggestions for brands to appropriately use DHA to build brand fans effect.

The United Arab Emirates (UAE) offers a level playing field to all ethnic entrepreneurs (EE’s) operating from within it. The purpose of this qualitative research case study is to explore the reasons underpinning the relatively greater success that Indian-origin EE’s in the UAE have been enjoying for sustained periods – and across diverse industries – relative to their counterparts belonging to several other nations.

Qualitative research case study that draws from data gathered through 30 interviews of participants identified through expert sampling.

Whereas the UAE treats all its ethnic entrepreneurs (EE’s) alike and provides them with a level platform to operate from, the EE’s from India have consistently been outperforming those from all other nations, particularly within the context of the UAE’s large businesses spanning diverse industries. Three features seem to explain their success: their high tolerance for ambiguity; thriftiness; and intercultural competence.

Two key limitations were faced: firstly, the negligible research literature on ethnic entrepreneurship in the UAE, and related official statistics such as details (by ethnicity/nationality) of EE-owned businesses, and secondly, the industry-wise break down of such businesses and their performance, as available in other developed nations hosting EE’s. Resultantly, alternate sources of data have been used to complete this research.

Given the UAE’s national-level institutionalised efforts to promote entrepreneurship amongst its citizens and wider populace, there are many implications that this study holds for existing and future entrepreneurs.

While on the one hand, the UAE and the wider Gulf Cooperation Council region have been witnessing frenetic ethnic entrepreneurial activity in the past decade, the research literature on the regions’ ethnic entrepreneurship is extremely patchy. This case study serves to significantly bridge this gap, and to the best of the authors’ knowledge, this is the first work, that extensively explores the entrepreneurial trajectory of Indian EE’s in the UAE, and the factors driving their success.

Sustainability research has become important than ever, due to the visible effects of business operations on the environment, and the increasing green consciousness among the various stakeholder groups. These stakeholder groups mount pressure on organizations, to inculcate sustainable practices in their operations. In light of the stakeholder-resource-based view, this paper aims to examine the direct effect of stakeholder pressure on sustainability information disclosures. The mediation effect of perceived benefits in the nexus amidst stakeholder pressure and sustainability information disclosures was also assessed. Lastly, the paper assessed the moderation effect of sustainability knowledge in the nexus between perceived benefits and sustainability information disclosures.

This research is quantitative in nature. Structured questionnaire was deployed as the data collection tool. Small and Medium Enterprises in Ghana formed the population. Data set from 258 Ghanaian small and medium enterprises was analyzed by the use of structural equation modeling.

Contrary to expectation, the study revealed that the effect of stakeholder pressure on sustainability information disclosures is positive, but statistically insignificant. The nexus between stakeholder pressure and sustainability information disclosures was revealed to be fully mediated by perceived benefits. Lastly, sustainability knowledge was revealed to positively moderate the relationship amidst perceived benefits and sustainability information disclosures.

This paper contributes to sustainability literature by demonstrating how stakeholder pressure influences sustainability information disclosures in the context of small and medium enterprises in an emerging economy.

The rapid development and widespread application of artificial intelligence tools have raised concerns about how designers are embracing these technologies. This study investigates the factors influencing designers' behavioral intention to use and disclose the use of generative artificial intelligence.

A quantitative research approach was employed, designing a structured questionnaire based on Self-Determination Theory to assess the impact of various psychological and social dimensions. The questionnaire included dimensions such as autonomy, competence, relatedness, social influence, value fit and social innovativeness. A Partial Least Squares Structural Equation Modeling analysis was conducted on 309 valid responses from diverse design fields.

Competence and relatedness are significant factors influencing designers' continuance intention to use generative artificial intelligence. Although autonomy does not significantly affect continuance intention, it plays a crucial role in the decision to disclose artificial intelligence participation. Social influence and value fit significantly shape autonomy, competence and relatedness, while the impact of social innovativeness is relatively limited.

This study clarifies the factors influencing designers' continuance intention and disclosure of generative artificial intelligence tools from both individual and social dimensions, enhancing the understanding of the relationship between designers and generative artificial intelligence tools. It provides valuable insights for the development of artificial intelligence technology and the future trends in the design industry, offering significant theoretical and practical value.

In recent years, there has been growing interest in the use of stainless steel (SS) in reinforced concrete (RC) structures due to its distinctive corrosion resistance and excellent mechanical properties. To ensure effective synergy between SS and concrete, it is necessary to develop a time-saving approach to accurately determine the ultimate bond strength τ_u between the two materials in RC structures.

Three robust machine learning (ML) models, including support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost), are employed to predict τ_u between ribbed SS and concrete. Model hyperparameters are fine-tuned using Bayesian optimization (BO) with 10-fold cross-validation. The interpretable techniques including partial dependence plots (PDPs) and Shapley additive explanation (SHAP) are also utilized to figure out the relationship between input features and output for the best model.

Among the three ML models, BO-XGBoost exhibits the strongest generalization and highest accuracy in estimating τ_u. According to SHAP value-based feature importance, compressive strength of concrete f_c emerges as the most prominent feature, followed by concrete cover thickness c, while the embedment length to diameter ratio l/d, and the diameter d for SS are deemed less important features. Properly increasing c and f_c can enhance τ_u between ribbed SS and concrete.

An online graphical user interface (GUI) has been developed based on BO-XGBoost to estimate τ_u. This tool can be utilized in structural design of RC structures with ribbed SS as reinforcement.