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This paper aims to examine the factors associated with a household business entrepreneur’s decisions to formalise the firm at a multidimensions level.

The data set is a panel of 2,336 SMEs and household businesses from Vietnamese SME surveys during the 2005–2015 period.

This study elucidates how firm-level resources, entrepreneur characteristics and costs of doing business influence an entrepreneur’s decision to enter, the speed and the degree of formality.

This study provides insight into the origins of an entrepreneur’s decisions to the multidimensions of business formality through the lenses of the resource-based view, entrepreneurship and institution theories.

This paper investigates whether board gender diversity is associated with the propensity to prioritize environmental issues in the material topic list on Global Reporting Initiative (GRI)-based reports.

Regressions analyses are performed using a sample of 755 firm-year observations from Italy over the 2018–2022 period. The data were obtained from hand-collection on GRI-based reports and Refinitiv Eikon database. Board gender diversity is measured through three proxies: the natural logarithm of the number of women directors, the ratio of female representation on board and the Blau index reflecting the proportion of women/men on board. Additional tests are also developed.

Results show that board gender diversity positively influences the propensity to rank environmental issues at the top of the material topic list on GRI-based reports.

Since the study focuses on the Italian context, results cannot be subjective to an extensive generalization to other countries.

This study highlights the importance of strengthening the female participation on board to prioritize the firm’s impact on environment within the materiality assessment of sustainability reporting.

To the best of the authors’ knowledge, this study is the first to investigate the association between board gender diversity and the highest ranked environmental material topics, thus contributing to better understand the role of women directors on materiality assessment within sustainability reporting.

This research investigates how consumers who are most active on Facebook during the day vs in the evening differ, differ in their ad consumption, and how advertising effects vary as a function of a key moderator: gender.

Using a survey of 281 people, the research identifies Facebook users who are more intensely using mobile social media during the day versus in the evening, and measures five Facebook mobile advertising outcomes: brand and product recall, clicking on ads, acting on ads and purchases.

The results show that women who are using social media more intensely during the day are more likely to use Facebook to seek information, hence, Facebook mobile ads tend to be more effective for these users compared to those in the evening.

This contributes to the literature by analyzing how the time of day affects social media behavior in relation to mobile advertising effectiveness, and broadening the scope of mobile advertising effectiveness research from other than just clicks on ads to include measures like brand and product recall.

By analyzing the effectiveness of mobile advertising on social media as a function of the time of day, advertisers can be more targeted in their media buys, and so better use their social media budgets, i.e. advertising is more effective for women who use social media (Facebook) more intensely during the day than for those who use social media more intensely in the evening as the former tend to seek more information than the latter.

This research extends media ecology theory by drawing on circadian rhythm research to provide a first demonstration of how the time of day relates to different uses of mobile social media, which in turn relate to social media mobile advertising consumption.

While research on social media advertising has been steadily increasing, little has been explored on how users consume ads when they engage with social media at different periods along the day. This paper extends media ecology theory by investigating time of day, drawing on the circadian rhythm literature, and how it relates to social media usage.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.