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The study investigates the impact of various factors on the number of active investors in digital health startups. Through nine hypotheses, we examine the influence of metrics such as patents, online presence, financial aspects and company valuation on investor interest. The results reveal positive associations between these metrics and investor numbers, highlighting their role in signaling strength and attracting investment. This research enhances the understanding of investor valuation in digital health startups, emphasizing the importance of credible signals for building trust and securing funding. However, we acknowledge limitations in data analysis methods and suggest future research to explore industry signals, longitudinal trends and failed startups for comprehensive insights.

This study delves into the design methodology and approach, aiming to fill gaps in understanding investor roles in valuing digital health ventures. We focus on deciphering factors driving valuations for these startups to secure growth financing. Using signaling theory, we investigate how entrepreneurs communicate their latent strengths to bridge information gaps, aiding investment decisions. We analyze a sample of 482 healthcare startups from the Pitchbook database using Poisson regression in SPSS.

This research sheds light on the factors driving investor interest in digital health startups. Despite the critical role of entrepreneurs in patient care innovations, the relationship between investor characteristics and funding for digital health technologies still needs exploration. We examine factors influencing investor valuation in healthcare startups and identify patents, social followers and financial disclosures as pivotal elements shaping investor interest. The findings show that all factors for active investors are significant for all variables except similar unique visitors.

These results significantly enhance our understanding of investor decision-making in digital health startups. They confirm the importance of various signals, like patent activity, online presence and financial performance, in attracting investor attention. We utilize unique data sources, offering insights into investors' behavior across different funding stages. In conclusion, these findings underscore investors' crucial role in the growth and funding of healthcare tech startups, emphasizing the need for robust signals to attract investment.

Intellectual capital (IC) and venture capital (VC) play an important role in enterprise development. While the literature has investigated the relationship between IC and the profitability of companies, the relationship among IC, VC and enterprise value (EV) is still not well understood.

Drawing insights from the literature, we develop a few testable hypotheses about the relationships among IC, VC and EV. Using the panel data of companies listed in the Chinese stock market from 2009 to 2019, we employ fixed-effects regression models to test these hypotheses.

We find that IC has a significant positive effect on long-term EV. VC is found to have a positive direct effect on long-term EV but has a negative direct effect when its moderating effect with IC is considered. To explain this finding, we develop a simple economic model and provide an over-investment perspective.

We believe this paper can shed light on pro-venture investment policies in China, as well as provide indications for similar policies around the world.

Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.

This paper believes that while implementing the gradual delay retirement age policy in China, the impact should be considered comprehensively; we should pay attention to impacts brought by the delayed retirement policy and introduce policies to deal with the impacts in a timely manner.

This paper aims to explore the delayed retirement’s impact on women’s labor supply and to clarify the elderly care’s role in it.

The results found that the delayed retirement has a positive effect on the women’s overall and young women’s labor supply, with a more significant promotion for young women’s labor supply. The mediation results suggest that delayed retirement promotes women’s labor supply by affecting elderly care. Therefore, we believe that while implementing the gradual delay retirement policy in China, it is important to implement it on the correct estimation basis so as to reduce the volatility in the labor market.

This paper may produce marginal contributions in the following two aspects: From the research perspective, we construct a model containing delayed retirement, elderly care and women’s labor supply and illustrate how the delayed retirement promotes women’s labor supply by affecting elderly care. Secondly, from the research content, this paper expands the delayed retirement on macro-employment and further explores the micro-impact on employment.

We aim to provide a systematic literature review of the determinants and consequences of labor investment efficiency in an international context. First, we offer a theoretical discussion of labor investment efficiency, followed by an examination of its measurement. Next, we review the determinants of labor investment efficiency, categorizing them into firm fundamentals including financial reporting quality, governance and controls, corporate social responsibility/environmental regulation and macroeconomic determinants. Finally, we review the limited empirical literature on the consequences of labor investment efficiency. We also provide some suggestions for future research.

We perform a systematic literature review using the Preferred Reporting Items for a Systematic Review of Meta-Analysis (PRISMA) guidelines to examine archival studies investigating the determinants and consequences of labor investment efficiency. Using a Boolean search strategy on the Scopus and PRISMA selection criteria, we review 86 published archival research articles from 2014 to the end of August 2024.

Our review highlights that firm-level fundamental factors including financial reporting quality have profound implications for labor investment efficiency. Effective governance mechanisms also help mitigate agency conflicts and information asymmetries and alleviate labor investment inefficiencies. Furthermore, the influence of regulations including ESG-related regulations and macroeconomic factors play a crucial role in shaping labor investment decisions. We find very little research on the consequence of labor investment efficiency.

Our review has highlighted that well-functioning corporate governance tools are effective in mitigating inefficient labor investments. Stakeholders, therefore, should ensure that firms have effective internal governance mechanisms in place and that external governance regulations complement and where necessary act as substitutes for internal governance mechanisms to optimize labor investments.

To the best of our knowledge, this study represents the first systematic review of extant research on labor investment efficiency. Our review highlights some research gaps, particularly about the consequences of labor investment efficiency and offers some suggestions for future research.

Additive manufacturing offers the ability to produce complex, flexible structures from materials like thermoplastic polyurethane (TPU) for energy-absorption applications. However, selecting optimal structural parameters to achieve desired mechanical responses remains a challenge. This study aims to investigate the influence of key structural characteristics on the energy absorption and dissipation behavior and the deformation process of 3D-printed flexible TPU line-oriented structures.

Samples with varying line orientations and infill densities were fabricated using material extrusion and subjected to quasi-static compression tests. The design of experiments methodology explored the significance of design variables and their interaction effects on energy absorption and dissipation.

The results revealed a statistically significant interaction between infill density and orientation, highlighting their combined influence; however, the effect was less pronounced compared to infill density alone. For low-density structures, changing the orientation from 0°/90° to 45°/−45° and increasing infill density enhanced energy absorption and dissipation, while high-density structures exhibited unique energy absorption behavior influenced by deformation patterns and heterogeneity levels. This study facilitates the prediction of mechanical responses and selection of suitable TPU line-oriented printed parts for energy absorbing applications.

To the best of the authors’ knowledge, the present work have investigated for the first time the energy-related responses of flexible line-oriented TPU structures highlighting the distinction between the low and high density structures.