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Prior studies suggest that, in an industry in which several public firms operate (i.e. greater public firm presence), uncertainty about business operations within the industry is reduced due to greater analyst coverage and quality of information disclosure. In this study, the authors examine how UK private firms respond to investment opportunities in fixed intangible assets (FIAs) in an environment characterised by greater public firm presence (PFP).

Using data from 61,278 (1,358) private (public) UK firms operating in ten sectors spanning from 2006 to 2016, the authors conduct this analysis by using panel econometric techniques.

The authors observe that private firms are more responsive to their FIA investment opportunities when they operate in industries with more PFP. Also, the authors find that firms in industries with better information quality use more debt and have longer debt maturity security but less internal cash flow. Overall, the findings indicate that PFP generates positive externalities for private firms by lessening industry uncertainty and enhancing more efficient FIA investment. The results are robust to endogeneity concerns.

A key limitation of the study is that it focuses on a single country (the UK) and therefore there is a likelihood that the results found are specific to this setting but not others, particularly developing and emerging economies. Thus, future studies could explore these ideas from the viewpoint of multiple countries.

Overall, the study demonstrates the importance of information disclosure in driving investment decisions of firms.

While this paper builds on the information disclosure and corporate investment literature, it is one of the first attempts, to the best of the authors’ knowledge, to explore how private UK firms respond to investment in FIAs in an environment characterised by greater PFP.

Venture capital (VC) is an essential element in healthy entrepreneurial environments; therefore, many countries in developing entrepreneurial economies support the industry via direct or indirect government interventions. The purpose of this study is to examine through the example of the Hungarian market, whether direct or hybrid state involvement has contributed more to the growth of the invested enterprises. The findings are relevant in the design of government VC schemes and in the contracts mitigating the moral hazards inherent in government funding.

The basis of empirical research is a unique hand-collected database covering Hungarian government-backed VC (GVC) investments. Based on the financial data of investee firms, the authors investigate whether firms financed by hybrid VC involving market participants are able to outperform firms that receive pure public financing using panel regression.

Based on Hungarian evidence, hybrid VC-backed firms generated lower growth and employment than their purely government-backed peers. Both schemes showed meagre innovation activity. The conclusion is that because of the conflict of private and economic policy objectives in hybrid financing, the exposure of hybrid risk capital to moral hazard is higher than that of pure public financing. Private interests in hybrid funds can only improve investment efficiency if they are structured along the lines of market-based independent financial intermediation and the contracts imitate the ones existing amongst limited and general partners in private schemes.

The research covers the data of Hungarian government-backed firms by tracking the full range of 86 investments made in the purely government scheme and 340 firms that received funding in the hybrid scheme. The research focuses on two government initiatives, and the results are influenced by the specific regulation of the programs; therefore, the results cannot be generalized for all government agendas; they are indicative in the designs of the agendas.

There is a limited number of empirical studies investigating the impact of VC in developing markets, especially in the Central and Eastern Europe region. This firm-level research on the impact of public VC can help improve the effectiveness of development policies. By analysing the entirety of investments of a VC program that is near to its completion, the authors provide new insight into the efficiency and prospects of GVC schemes in the region.

Impact investors differ from venture capital firms as they invest to create social and commercial value. This paper pursues the question: how do impact investors select social enterprises? The aim of this study is to understand the selection and investing process of impact investors.

This study developed a database of 115 impact-investing firms across different geographies. Emails were sent to investors associated with each of the impact-investing firms found in the database, out of which 32 replied with consent for a telephonic or in-person interview.

The significant findings presented in the paper are the following. First, this study shows the impact-investing selection process model. The four major steps in the selection process are context, investment focus, venture analysis and decision. In each step, social values and missions become the defining characteristics of the selection process. Second, the findings also discuss the typologies of impact investors as a function of their selection approaches.

This paper discusses the impact investing strategy among social enterprises. It provides a framework for impact investing among investee social enterprises. As an impact investing professional, one learns investment strategy through this paper.

Impact investing is a growing field. It is believed that impact investing could greatly impact sustainable development goals, climate change goals and help in inclusive development. This study helps to further understand impact investing process and hopes to help social enterprises and impact investors make a better match, thereby, creating a greater overall social and environmental impact.

This study helps both practitioners and academics to understand the complexity of impact investing. This study helps develop heuristics that impact investors may use to make investments. This study provides a framework for investing, which the impact investing firms may use to invest.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

This instrumental case study (Stake, 1995) explores the benefits experienced by mentor teachers who mentored resident teachers in a year-long residency program.

The study was grounded by the Benefits of Being a Mentor conceptual framework, as defined by Ragins and Scandura (1999). The participating mentor teachers engaged in semi-structured interviews and a focus group. The data were analyzed through inductive and deductive data analysis techniques.

Using inductive and deductive data analysis techniques, three themes emerged on the benefits of being a mentor teacher: (1) extra support in the classroom, (2) professional learning and growth opportunities, and (3) investing in the future of education. The teachers’ perceived benefits were related to the connectedness of their personal and professional growth, the growth of the resident teachers and their students’ learning.

Mentor teachers play a vital role in teacher residency programs, as they are the primary influence on their resident teachers’ pedagogical praxis. In a residency program, mentor teachers support resident teachers’ sustained teaching experience by hosting them for one full academic year in their classrooms; therefore, exploring the benefits they receive from serving in this role is essential.

Countries worldwide aim to improve their comparative advantages by efficiently using scarce resources for economic growth and development. While many studies have been conducted to measure intellectual capital at the firm's level, measuring it at the national level has been under-examined. In addition, while the important role of national intellectual capital in economic growth has been theoretically recognized in literature, this important link has largely been ignored in empirical analyses.

This study uses the newly developed index of national intellectual capital from Vo and Tran's (2022) study to examine its effects on national economic growth in the long run. The dynamic common correlated effects technique and the pooled mean group estimation are used on the sample of 23 economies in the Asia–Pacific region from 2000 to 2020.

Findings from this study confirm the positive and significant contribution of the national intellectual capital to economic growth in the region. The authors also find that, as a feedback effect, economic growth will also enhance and improve the accumulation of national intellectual capital.

The findings of this paper provide valuable evidence and implications for policymakers in managing and improving national intellectual capital in the Asia–Pacific region.

To the best of the authors’ knowledge, this is the first empirical study to examine the impact of national intellectual capital on economic growth in the long run in the Asia–Pacific economies.

Many studies have analysed the impact of various variables on the ability of companies to raise capital. While most of these studies are sector-agnostic, literature on the effects of macroeconomic variables on sectors that established over the last 20 years like property technology and financial technology, is scarce. This study aims to identify macroeconomic factors that influence the ability of both sectors and is extended by real estate variables.

The impact of macroeconomic and real estate related factors is analysed using multiple linear regression and quantile regression. The sample covers 338 observations for PropTech and 595 for FinTech across 18 European countries and 5 deal types between 2000–2001 with each observation representing the capital invested per year for each deal type and country.

Besides confirming a significant impact of macroeconomic variables on the amount of capital invested, this study finds that additionally the real estate transaction volume positively impacts PropTech while the real estate yield-bond-gap negatively impacts FinTech.

For PropTech and FinTech companies and their investors it is critical to understand the dynamic with mac-ro variables and also the real estate industry. The direct connection identified in this paper is critical for a holistic understanding of the effects of measurable real estate variables on capital investments into both sectors.

The analysis fills the gap in the literature between variables affecting investment into firms and effects of the real estate industry on the investment activity into PropTech and FinTech.

Human capital is a portfolio of rich skills that the labour possesses. Human capital has attracted significant attention from scholars. Nevertheless, empirical findings on the utility of human capital have often been divided. To address the research gap in the literature, the authors attempt to understand how human capital plays a significant role in financial development and economic growth nexus.

The authors rely on secondary data published by the World Bank. The authors use econometric tools such as the autoregressive distributive lag (ARDL) model and related statistical tests to study the relationship between human capital, India's financial growth and gross domestic product (GDP) growth.

Study findings suggest that human capital and financial development contribute significantly to economic growth. Further, the authors found that human capital has a positive and significant moderating effect on the path of joining financial development and economic growth.

The study contributes to the human capital debate. Despite the rich body of literature, the study based on World Bank data confirms the previous findings that investment in human capital is always useful for the financial and economic growth of the nation.

This paper reveals some unique findings regarding effect of financial development and economic growth nexus which opens the window of new dimension to think about their nexus. It also provides a different pathway to foster the economic growth by using human capital and financial development as together, especially in India.

The first objective of this article is to analyse the reasons to pursue inclusive growth, that is economic growth accompanied by a reduction of social inequalities in different dimensions. The second objective of the article is to develop a systematised framework to understand the different channels and enablers by which heritage can contribute to inclusive growth through a review of specialised literature.

The methodology of this article is based on an exhaustive review of existing literature around models of economic development and their ability to decrease social inequalities. It critically reviews theoretical and empirical studies on existing economic approaches and links them with the heritage policy field.

The article finds that countries should pursue inclusive development since it is a fundamental condition for social cohesion, trust and society's overall well-being and because it enables economic growth to be sustainable through time. It also identifies four channels through which heritage can contribute to inclusive development: in its public good dimension, in its capacity to equalise opportunities, in its ability to reduce social, educational and health disparities and in its capacity to decrease spatial income inequalities through regeneration processes.

The framework, that is developed to categorise the different channels and enablers through which heritage could contribute to inclusive growth, is not empirically tested. Further research could approach this by estimating a difference in difference model. However, data limitations could limit this objective in the short-term.

Its originality relies in the development of a conceptual framework that is aimed at shaping heritage policies that target, at the same time, the reduction of inequalities and economic growth.

This study examines the impact of firm-specific and macroeconomic factors on the working capital behavior of firms listed in the Middle East and North African (MENA) region.

This study is based on a panel data analysis of 687 firms listed on 11 MENA markets, carried out using the Generalized Method of Moments (GMM) approach.

The results of this study reveal that profitable firms with high levels of operating cash flows adopt a conservative working capital management. Young firms with rapid growth rates, highly leveraged firms and firms with large investments in fixed assets have higher liquidity needs, which explains their tendency to pursue aggressive working capital strategies. Similarly, large firms exercise their bargaining power over their clients and suppliers to implement an aggressive approach of working capital management. Finally, firms do not have the luxury to decide how working capital should be managed when they are subject to outside macroeconomic forces that affect their stakeholders as well.

The findings of this study can help managers adopt efficient practices and identify optimal working capital levels. Firms in the MENA region maintain excess reserves of cash, which causes under-investment and inefficient allocation of resources in the economy. Improving working capital management practices can allow firms to regain operational efficiency, enhance financial performance and support economic growth.

To the best of the authors' knowledge, this study investigates this topic in MENA emerging markets and contributes to enriching the existing corporate finance literature in emerging markets.