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This paper examines household and community characteristics that influence the entry of rural households into non-farm entrepreneurship and investigates the various factors that influence the market exit of non-farm enterprises (NFEs).

The authors use data from three rounds (2011/12, 2013/14 and 2015/16) of the World Bank’s Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The authors employ panel logit and multilevel logit models to examine the probability of opening one or more enterprises and the enterprise exit rates.

Results indicate that the likelihood of starting a NFE is positively associated with primary education attainment, access to credit, experiencing idiosyncratic shocks and availability of formal financial institutions. Age, higher education attainment and rising farm input prices constrain entry into non-farm entrepreneurship. The enterprise exit rate is negatively associated with small-town residence, wealth, access to tar/gravel roads and cellphone communication.

Policymakers and administrators should strive to address the challenges that communities face in transportation, communication and financial services. Policies aimed at stabilizing prices and increasing access to mobile communication, primary education and road infrastructure could help expand the rural non-farm sector.

Previous studies primarily examined the determinants of participation in NFEs at a given time using cross-sectional data. The current study uses panel data to study the dynamics of NFE ownership by investigating households’ decisions to enter into or exit from the sector.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-09-2022-0611

Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.

Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.

Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.

This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.

This paper examines whether target returns act as specific goals that impact risk-taking when individuals make investment decisions.

Using an experimental setting, the authors assign either a low or a high target return to participants and ask them to make independent investment decisions as the risk-free rate fluctuates around their target return and, for some of them, becomes negative.

Building on cumulative prospect theory, the authors find that the prevailing reference point of participants is the target return, regardless of the level of the risk-free rate. This result still holds even when the risk-free rate is negative, suggesting that (1) the target return drives risk-taking more than does a zero-threshold and (2) negative rates are limited as a tool to stimulate appetites for risk. In a follow-up study, the authors show that these conclusions remain valid when the target return is endogenously determined.

The authors' original approach, which pioneers the use of target returns in both the positive and negative interest rate contexts, provides insightful results about the “reach for yield” among regular people.

This paper aims to examine the effect of critical mass of women managers on corporate boards on the voluntary disclosure of climate change in a developing country in which the regulations on climate change disclosure is an area of growing research interest.

This study uses logistic panel regression models with a sample of 1,001 firm-years for companies in the Borsa Istanbul 100 Index that were asked to disclose voluntary climate change indicators over the seven-year period from 2014 to 2020 through the Carbon Disclosure Project.

This paper provides evidence from an emerging country that the critical mass of women on the board has no impact on voluntary climate change disclosure. In addition, the presence of independent managers on the board was found to have a significant impact on climate change disclosure. In addition, the results show that larger companies are more likely to report their climate change activities. Large companies are more visible due to their size, are perceived by stakeholders as more polluting and are, therefore, more likely to report on the environment.

The results show that the critical mass of women on the board has no effect on voluntary disclosure of climate change. Empirical tests are still needed to strengthen the overall validity of the critical mass of at least three women on boards in Türkiye.

Despite many valuable insights provided by critical mass theory, very few studies directly address critical mass and voluntary disclosure of climate change. To the best of the authors’ knowledge, this study is the first empirical and comprehensive paper in the Turkish context evaluating critical masses and voluntary corporate climate change giving a comparison between firms listed on financial industry and nonfinancial industry.

The intensity of carbon emissions has led to the serious problem of global warming, and the consequences in terms of climatic disasters are gaining increasing attention worldwide. As the energy sector is responsible for most global emissions, developing clean energy is crucial to combat climate change. This study aims to examine the relationship between corporate governance and renewable energy (RE) consumption and explore the interaction between RE production and RE use.

The study adopts an econometric framework of a panel model, followed by the robustness check using alternative methods, including logit regressions. The bivariate probit model is used to analyze the interaction between the decision to use and the decision to produce RE. The analysis is based on a sample of 3,896 firms covering 45 countries worldwide.

The results reveal that appropriate governance mechanisms positively impact RE consumption. These include the existence of a sustainability committee; environmental, social and governance-based compensation policy; financial performance-based compensation; sustainability external audit; transparency; board gender diversity; and board independence. Firms with appropriate governance mechanisms are more likely to produce and use RE than others. Finally, while RE use positively impacts firm value and environmental performance, the authors find no significant effect on current profitability.

This study goes beyond previous research by exploring the impact of multiple governance mechanisms. To the best of the authors’ knowledge, this is also the first study examining the relationship between RE use and firm value. Overall, the findings suggest that RE transition requires, first of all, establishing appropriate governance mechanisms within companies.

This study aims to investigate the adaptation strategies they practice and the factors that influence their use of adaptation strategies.

The mixed-method sequential explanatory design was used to triangulate the data collected. Multistage sampling was used to select 400 sampled households for household surveys. Eight focus groups, each with eight to ten participants, and 24 key informants, were specifically chosen based on their farming experiences. Chi-square tests, one-way ANOVA and a binary logit model were used to analyze the data.

The majority of farmers used simple and low-cost adaptation strategies like changing planting dates, selling livestock and off-farm and nonfarm work. A minority of farmers used advanced adaptation strategies like crop diversification and water harvesting for irrigation. The result further revealed that: the age of the household head, educational status of household heads, farm size, livestock ownership, farming experiences, household income, access to credit and access to climate information significantly influenced the adoption of the adaptation strategies. Public policy should provide water harvesting and irrigation technology, climate-related information and the provision of microcredit facilities to enhance the farmers’ resilience to climate change risks.

Although several studies on climate change adaptation strategies are available, this paper is one of the few studies focusing on a particular agro-ecological zone, an essential precursor to dealing with current and projected climate change in the area. It provides helpful insights for developing successful adaptation policies that improve adaptive capacity and agricultural sustainability in southern Ethiopia’s lowlands.

The authors measure the cost of equity to earnings yield differential for a sample of 2,035 non-financial firms. In a series of Logit and Tobit regressions, the authors examine if the cost of equity to earnings yield differential is related to dividend policy in the manner predicted by agency theory.

Agency theory says a firm's optimal dividend policy is partially determined by the relationship between the earnings yield and the cost of equity capital. When the cost of equity is higher (lower) than the earnings yield, firms are motivated to (not) pay dividends as this reduces the cost of capital and holding other things constant, increases corporate valuations. The authors test whether managers set dividend policies to maximize the value of the firm.

The study’s findings show that when the cost of equity is higher (lower) than earnings yield, firms are more (less) likely to be dividend payers and the payouts are higher (lower). The results are robust to the inclusion of share repurchases as an alternative to cash distributions. The study’s findings support the cost of equity hypothesis and are consistent with alternative dividend theories.

The study’s findings support the cost of equity hypothesis and are consistent with alternative dividend theories. To the authors’ knowledge, this is the first paper testing the cost of equity hypothesis.

This study attempts to examine the relationship between board characteristics and dividend payout decisions of conventional and Islamic banks.

This study employed unbalanced panel data of both Indonesian conventional and Islamic banks over the period 2008–2021, estimated using tobit and logit models. Dividend payout decisions were measured using the dividend payout ratio and probability to pay dividends. Meanwhile, board characteristics were represented by board size, board independence, board gender diversity, board meeting, board chairman tenure and board chairman tenure.

The results show that, in the context of conventional banks, board meetings, board chairman tenure and board chairman tenure are correlated with higher dividend payout decisions, while board gender diversity indicates lower dividend payout decisions. On the other hand, in the context of Islamic banks, board size and board meetings are associated with higher dividend payout decisions, while board independence and board chairman tenure are related to lower dividend payout decisions.

This study fills the gaps in the literature on bank dividend policy. It also provides additional insights regarding the relationship between board characteristics and dividend payout decisions in the context of conventional and Islamic banks. In addition, this study gives essential contributions to regulators and investors of both banks, especially in a developing country, Indonesia.

This study is one of the first to provide empirical results regarding the relationship between board characteristics and dividend payout decisions of conventional and Islamic banks. Board characteristics are indicated as one of the fundamental factors that determine dividend payout decisions of both conventional and Islamic banks in Indonesia.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

This paper aims to extend the scope of previous studies on education-occupation mismatch to explicitly focus on the role high school track choices have on the risk of being mismatched in the labor market.

The paper uses the most exhaustive available database regarding the early-career paths of university graduates in Romania. Using a novel matching technique, entropy balancing (EB), our study relies on multinomial logit models and logit regressions to estimate the effect of the completed high school track on the likelihood of being mismatched in the labor market. The empirical analysis focuses on two types of education-occupation mismatches: horizontal and vertical mismatches.

We show that studying a different field in college compared to the completed high school track increases the risk of being skill mismatched in the first job after graduation. Five years after college graduation, the influence of the high school track fades, while being skill mismatched in the first employment plays a more important role. In contrast, we find no evidence that pursuing a college major unrelated to the completed high school track increases the probability of being overeducated. However, being overeducated in the first job increases the risk of being overeducated five years later.

The study brings new reliable evidence on the extent to which high school track choices may contribute to the risk of being mismatched in the labor market.