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Racial wealth inequality is a significant and growing issue in the USA. Improving the lagging rate of black new venture creation and successful entrepreneurship could help close the gap. The purpose of this paper is to focus needed attention on the financial challenges resulting from institutional and systemic discrimination that black entrepreneurs must deal with. Following this literature review, the paper makes recommendations and broad public policy suggestions.

This study conducts a literature review and discusses the myriad of reasons black entrepreneurs struggle with inadequate access to capital, with special emphasis on weaker entrepreneurial ecosystems that have resulted from systemic racism.

The paper sheds light on several factors which continue to directly impede successful black entrepreneurship including discrimination in lending, distrust in institutions, over-reliance on (inadequate) personal capital and declining black-owned banking and financial institutions, as well as community banking options in black communities.

The paper is conceptual and relies on prior literature. The proposed solutions are just a starting point and are certainly not meant to be all-inclusive or comprehensive. Much future research, particularly longitudinal research, is needed to further develop theory and specific public policies which can close the disparities this study has discussed. This study outlines several key areas in need of further quantitative and qualitative studies to better understand black entrepreneurship.

The US economy will increasingly suffer if the nearly 15% of population (and growing) made up of black communities continues to struggle. The broad-based policy solutions proposed in this paper would allow for increased access to capital that would address the long-term deficiencies and help to close the racial wealth gap.

Through this study’s broad-based potential solutions, entrepreneurial ecosystems can be strengthened to build the environment for successful new venture creation in black communities. The longer-term benefit would be increased tax revenues, improved communities with fewer individuals needing support through government assistance and greater social stability as economic gaps between various racial groups are closed.

Using a broader entrepreneurial ecosystem framework and a systemic racism theory lens, this study discusses the limited capital black entrepreneurs have access to. Following this literature review, this study offers broad-based policy solutions that can strengthen ecosystems and directly address the issues raised in the paper.

Ukraine hosts thousands of international students for educational tourism, of which more than 18,000 Indian medical students were compelled to escape Ukraine under emergency conditions of war. This paper aims to examine their intention to return to Ukraine to complete their education based on an integrated theory of planned behaviour (TPB) framework with added constructs, i.e. risk perception, career anxiety, rescue and relief memory.

The data were collected from 26 February 2022 to 30 June 2022 in two phases and two modes. It was ensured that the respondents were strictly confined to Indian medical students who had travelled to Ukraine for educational tourism. SPSS 25 and AMOS 23.0 were used to analyse the data. The hypotheses proposed were statistically tested.

The analysis reveals that the extended TPB model resulted in a strong model and the empirical findings corroborate that the students’ attitude, subjective norms, perceived behavioural control and career anxiety significantly and positively influence the students’ revisit intention (RI) while risk perception and rescue and relief memory have a negative influence on the RI.

The study provides timely insights and implications to the Ukrainian tourism industry, particularly educational tourism business and medical institutions under the present turmoil, which can also act as blueprint research for destinations with a similar unstable political background.

The primary value of this research work is that it provides an understanding of the intention of medical students (educational tourists) towards revisiting the war-hit destination of Ukraine.

Assembly action recognition plays an important role in assembly process monitoring and human-robot collaborative assembly. Previous works overlook the interaction relationship between hands and operated objects and lack the modeling of subtle hand motions, which leads to a decline in accuracy for fine-grained action recognition. This paper aims to model the hand-object interactions and hand movements to realize high-accuracy assembly action recognition.

In this paper, a novel multi-stream hand-object interaction network (MHOINet) is proposed for assembly action recognition. To learn the hand-object interaction relationship in assembly sequence, an interaction modeling network (IMN) comprising both geometric and visual modeling is exploited in the interaction stream. The former captures the spatial location relation of hand and interacted parts/tools according to their detected bounding boxes, and the latter focuses on mining the visual context of hand and object at pixel level through a position attention model. To model the hand movements, a temporal enhancement module (TEM) with multiple convolution kernels is developed in the hand stream, which captures the temporal dependences of hand sequences in short and long ranges. Finally, assembly action prediction is accomplished by merging the outputs of different streams through a weighted score-level fusion. A robotic arm component assembly dataset is created to evaluate the effectiveness of the proposed method.

The method can achieve the recognition accuracy of 97.31% and 95.32% for coarse and fine assembly actions, which outperforms other comparative methods. Experiments on human-robot collaboration prove that our method can be applied to industrial production.

The author proposes a novel framework for assembly action recognition, which simultaneously leverages the features of hands, objects and hand-object interactions. The TEM enhances the representation of dynamics of hands and facilitates the recognition of assembly actions with various time spans. The IMN learns the semantic information from hand-object interactions, which is significant for distinguishing fine assembly actions.

The study aims to identify the trends in the scholarly works on investors preference toward sustainable investments by synthesizing their knowledge structures.

A systematic search approach using PRISMA protocol on the Scopus database was used to generate a sample of 403 publications for the purpose of bibliometric analysis. The study performed a range of analyses, including three-field plot analysis, thematic mapping and cluster analysis using the VOSviewer and Biblioshiny software.

The key findings comprise the identification of four clusters within the subject, namely, corporate social responsibility and environmental, social and governance (ESG) investing, ethical investing, green finance and socially responsible investments. This study offers a clear picture of the publishing advancement and research diversification of four selected clusters' research themes, and cluster subthemes.

The research reveals the social and intellectual structure of the field, which provides the future researchers an insights into emerging themes and provides them opportunities for collaboration as well. The outcomes of the research hold significance for policymakers, governing bodies, aspiring scholars, advocates for the environment and investors. It offers an insightful framework for implementing sustainable practices, balancing profits, and environmental risks and creating value from environmentally conscious research and practice.

The future direction and extensiveness of research work have been explored using the themes generated. To the best of the authors’ knowledge, this study, which combines the VOSviewer and Biblioshiny tools, is likely the first attempt to provide a thorough bibliometric analysis in the research sphere of investors preferences toward sustainable investments.

The purpose of this study is to address the generalised lack of guidance on ethical treatment of corporate (e.g. non-research) data in higher education institutions, by focusing on the case of the University of Queensland (Brisbane, Australia). No actionable framework is currently available in the country to govern the ethical usage of corporate data. As such, this research takes a stakeholder-centred approach to data ethics; the lived experience of the stakeholders involved coupled with a theory-based ethical framework allowed the authors build to build a framework to guide ethical data practice.

Adopting a revised canonical action research approach focused on intervention on the context, the authors conducted a review of the literature on ethical usage of data in higher education institutions; administered one survey to university students (n = 168); and facilitated three workshops with professional staff (two) and students (one).

Collected data highlighted how, among other themes, the role and ethical importance of transparency was the dominant claim among all stakeholder groups. Findings helped the authors develop an Enhanced Enterprise Data Ethics Framework (EEDEF) emphasising transparency and stakeholder-centricity.

Legislation is the driver to regulate the use of corporate data in higher education; however, this can be problematic because legislation is retrospective, lacks normativity and offers scarce directions for cases that do not exactly follow within the legislative mandate. In light of these regulatory limitations, the authors’ EEDEF offers operators guidance on how to ethically manage corporate data in the higher education environment.

This study fills gaps in praxis and theory; that is the lack of literature and guiding ethical frameworks to inform data practice in higher education. This research fosters a more ethical data management by virtue of genuine and authentic engagement with stakeholders and emphasises the importance of strategic decision-making and maturity of data culture in the higher education sector.

Fast fashion brands in Asia are increasingly incorporating corporate social responsibility (CSR) into their business strategies in response to the mounting environmental and social concerns. The study aims to provide insights into the current landscape of CSR practices and communication within the Asian context through focusing on two prominent Asian brands to understand how these fashion brands articulate and convey their CSR activities on their respective websites.

This study used a qualitative content analysis to critically evaluate the CSR communication used by Uniqlo and Shein, with the incorporation of signalling theory as a theoretical framework to discuss the observed elements on their websites.

The results indicate that the two Asian fast fashion brands actively engage in CSR’s environmental and social dimensions. Notably, the social dimension is more prominently expressed on both brands’ websites than on other dimensions. Through a nuanced interplay of colour, imagery and keywords, these Asian fast fashion brands strategically signify their commitment to environmental stewardship and stakeholder well-being.

This study fills a gap in the literature by examining CSR programs on Asian-owned fast fashion brands’ websites through the application of signalling theory. The research contributes to the theoretical foundation of CSR communication outcome research, offering actionable insights for marketers entering the Asian fashion market to enhance brand reputation and legitimacy.