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This study aims to enrich the current theoretical debate on the growth of start-up firms by extensively investigating the ongoing empirical studies in this research stream. Moreover, this study identifies drivers whose support roles are confirmed in the literature and recommends further research opportunities.

In this study, we analysed the results of 316 empirical studies on start-up firms and growth and also identified and categorised 66 growth drivers. We presented these drivers in three-dimensional charts: 1) the frequency of using each driver in the 316 studies, 2) the consistency of each driver as measured by the number of studies supporting its statistical significance and 3) the net effect (positive or negative) of each driver on growth.

Our analysis compares extant studies on growth drivers and shows some under-explored growth factors of start-up firms.

Both start-up managers and policymakers can benefit from this study. This study provided managers with a fine-grained tool on the main growth drivers and can guide policymakers in supporting policies for start-up firms.

This study provides a rich, fine-grained and coherent picture of several potential growth drivers of start-up firms. Moreover, we extended our analysis to various potential drivers more than previous studies on this topic, thereby providing fruitful insights into the critical growth factors for start-up firms.

This study aims to explore the relationship between promoter share pledging and the company’s dividend payout policy in India. Furthermore, this study also analyses the moderating impact of family involvement in business on the association between share pledging and dividend payout.

A sample of 236 companies from the S&P Bombay Stock Exchange Sensitive (BSE) 500 Index (2014–2023) has been analysed through fixed-effects panel data regression. For additional testing, robustness checks include alternative measures of dividend payout and promoter share pledging, as well as alternative methodologies such as Bayesian regression. Lastly, to address potential endogeneity, instrumental variables with a two-stage least squares (IV-2SLS) methodology have been implemented.

Upholding the agency perspective, a significantly negative impact of promoter share pledging on corporate dividend payouts in India has been uncovered. Moreover, family involvement in business moderates this relationship, highlighting that the negative association between promoter share pledging and dividend payouts is more pronounced in family companies. The findings are consistent throughout the robustness testing.

The present study represents a pioneering endeavour to empirically analyse the link between promoter share pledging and dividend payouts in India. It enhances the theoretical underpinnings of the agency relationship, particularly by substantiating the existence of Type II agency conflicts between majority and minority shareholders. The findings of this research bear significant implications for investors, researchers and policymakers, particularly in light of the widespread prevalence of promoter-controlled entities in India.

The purpose of this paper is to contribute to the literature on secondary equity offerings (SEOs) by examining the impact of the Black Economic Empowerment (BEE) policy on secondary equity offering (SEO) pricing dynamics of South African Real Estate Investment Trusts (REITs).

With a sample of 152 SEOs of South African REITs from 2010 to 2020, ordinary least squares (OLS) models, fixed effect models, parametric and non-parametric tests were applied to test for the impact of BEE on the underpricing of SEOs.

Significant underpricing is discovered in highly compliant (BEE) REITs; in other words, SEOs pricing of BEE compliant REITs are more underpriced compared to non-compliant BEE REITs. With this, BEE compliant REITs and more so, highly compliant BEE REITs in particular leave more money on the table.

The government is therefore aware of the impact policy interventions play when REITs raise financing through SEOS. With these, highly compliant BEE REITs will need to be more strategic when making BEE compliance decisions as this is shown in our study to impact the underpricing of SEOs.

This is the first study to investigate SEO underpricing for the BEE policy using the South African REITs context.

Crystallization is the process widely used for components separation and solids purification. The systems for crystallization process evaluation applied so far, involve numerous non-invasive tomographic measurement techniques which suffers from some reported problems. The purpose of this paper is to show the abilities of three-dimensional Electrical Capacitance Tomography (3D ECT) in the context of non-invasive and non-intrusive visualization of crystallization processes. Multiple aspects and problems of ECT imaging, as well as the computer model design to work with the high relative permittivity liquids, have been pointed out.

To design the most efficient (from a mechanical and electrical point of view) 3D ECT sensor structure, the high-precise impedance meter was applied. The three types of sensor were designed, built, and tested. To meet the new concept requirements, the dedicated ECT device has been constructed.

It has been shown that the ECT technique can be applied to the diagnosis of crystallization. The crystals distribution can be identified using this technique. The achieved measurement resolution allows detecting the localization of crystals. The usage of stabilized electrodes improves the sensitivity of the sensor and provides the images better suitable for further analysis.

The dedicated 3D ECT sensor construction has been proposed to increase its sensitivity in the border area, where the crystals grow. Regarding this feature, some new algorithms for the potential field distribution and the sensitivity matrix calculation have been developed. The adaptation of the iterative 3D image reconstruction process has also been described.

This study investigates whether the disclosure of derivatives is value relevant in emerging markets and evaluates the effects of the 2008/2009 global financial crisis on the value relevance of derivative disclosures.

Panel regression models using sub-samples and a crisis interaction term were applied to a sample of the 200 largest non-financial firms by market capitalization listed on the Johannesburg Stock Exchange (JSE) from 2005 to 2017 to assess the consequences of the financial crisis.

The results suggest that the disclosure of derivatives is value relevant in the hitherto understudied context of emerging markets. The 2008/2009 financial crisis had a significant impact on derivatives use and the value relevance of derivatives disclosure by JSE-listed companies.

Companies should reconsider both how they employ derivatives as part of their risk management practices and how they communicate derivatives use to stakeholders in the financial statements. The findings facilitate a comparative analysis across various market contexts by researchers and assist investors in better decision-making. The findings can influence regulatory practices and can help standard setters to review disclosure requirements.

The benefits of corporate hedging were studied from an emerging market perspective, using an original dataset and approach to investigate the effects of international financial volatility on emerging markets. The authors tested whether companies are valued differently, based on their disclosure of the use of derivatives in the financial statements, and the effect of the financial crisis on the value relevance derivatives disclosures.

Technological advancements in games increased the popularity of online gaming. The rapid expansion of the eSports market may largely be attributed to the ever-increasing popularity amongst Generation Y amateur gamers. The primary objective of this study is to determine the factors influencing Generation Y amateur gamers' ongoing eSports gameplay intentions.

This study used the extended unified theory of acceptance as the theoretical framework. Data analysis included exploratory principal component analysis, confirmatory factor analysis and path analysis.

The results of the confirmatory factor analysis suggest that Generation Y amateur gamers' ongoing eSports gameplay intentions is an eight-factor model that is reliable, valid and has acceptable model fit. The results of the path analysis indicate that habit, price-value, flow, effort expectancy and facilitating conditions have a statistically significant positive influence on amateur gamers' ongoing eSports gameplay intentions, whilst social influence and hedonic motivation have a negative but non-significant influence on those intentions.

The sample was formed using only amateur eSports gamers. In this regard, the opportunity exists to research professional eSports gamers. This study only focussed on Generation Y members between 18 and 36 years old. As a result, there is an opportunity for researchers to research the different generations of South African eSports gamers to determine whether there are any differences or similarities between generational segments.

The results of this study clearly indicate that flow, together with habit are salient contributors to ongoing gameplay intentions amongst amateur eSports gamers in South Africa. A reasonable assumption that can be made here is that flow is also instrumental in encouraging habitual gaming, which increases the importance of flow in overall ongoing gameplay intentions. This suggests that R&D expenditure should be directed at enhancing user engagement by building increased levels of flow into eSports games.

eSports game developers can also achieve a desired state of flow by creating daily challenges that reward players when the players achieve specific objectives, which will encourage gamers to enter a state of flow when provided with challenges to complete. However, these in-game challenges should have a variety of levels regarding difficulty, ranging from beginner, intermediate and advanced levels so as not to exceed the effort expectancy of different groups of players. Game developers should provide regularly updated challenges to gamers to ensure that eSports games remain enjoyable and does not become predictable.

Given the nascence of research on eSports behaviour, the results of this study provide a novel addition to the knowledge pool, particularly in terms of amateur eSports behavioural intentions. Interestingly, hedonic motivation and social influence were non-significant negative predictors of Generation Y amateur gamers' ongoing eSports gameplay intentions. The recommendations provide various marketing strategies and opportunities for eSports business expansion.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

There has been significant growth in entrepreneurship research over the past several decades. Yet with all of the knowledge gained and presumably improved training of would-be entrepreneurs, firm failure rates remain persistently high. It is argued here that the historical and continued research focus on successful entrepreneurs has limited the field. Entrepreneurs are often considered to possess uniquely positive capabilities relative to the general population; this paper explores the possibility that the majority of entrepreneurs suffer from overconfidence and that this leads most entrepreneurs to make “bad bets” that result in underperformance and firm failure.

In this paper, a qualitative review of the literature was performed.

Based on the literature review, three formal propositions are developed. The first two suggest that the majority of entrepreneurs are overconfident in their personal capabilities and the prospects for their new ventures. It is then proposed that this overconfidence leads to errors in judgment that results in financial underperformance and failure found among most new ventures.

This paper makes an important contribution to the entrepreneurship literature by arguing that overconfidence negatively impacts pre-founding decision-making such that entrepreneurs pursue flawed opportunities. Studying the issues raised in this paper may spur new lines of research and knowledge that lead to better entrepreneurial outcomes.

This study presents and validates a theoretical model linking individual characteristics of the founding or lead innovative entrepreneur of a start-up venture – the entrepreneur's values, entrepreneurial attitudes and entrepreneurial self-efficacy – to the firm's entrepreneurial orientation (EO) and market orientation (MO) and, ultimately, to firm performance.

We conducted a survey on a stratified random sample of founders of early-stage South Australian micro- and small enterprises with a response rate of 24% (N = 204). Structural equation modelling was used to evaluate the model.

The study found that there is a significant relationship between the individual lead entrepreneur and firm strategies developed in early-stage firms in explaining firm performance. It also found that internal values are positively related to entrepreneurial attitude. Entrepreneurial attitude is positively related to entrepreneurial self-efficacy and EO innovativeness. In turn, entrepreneurial self-efficacy is related to innovativeness, proactiveness and risk-taking. The proactiveness dimension of EO and entrepreneurial attitude is related to MO. Entrepreneurial self-efficacy, innovativeness and MO are related to firm performance.

This research was limited to entrepreneurial ventures in South Australia and may lack generalisability in other states and countries.

The research contributes to the understanding of the heterogeneity within self-employed individuals, in particular among innovative entrepreneurs, by expanding insights regarding antecedents and consequences of the entrepreneurial process. It develops insights into the links of individual-level constructs with firm-level constructs to develop a more meaningful understanding of new venture creation and performance. It enhances our knowledge of the heterogeneity within the group of self-employed by exploring the individual entrepreneurial antecedents of performance in early-stage firms.