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Market sentiment has shown to influence housing prices in the global north, but in emerging economies, the nexus is rare to chance on in the current state of science for policy direction. More importantly in the recent decade where policymakers are yet to conclude on the myriad of factors confronting the housing market in sub-Saharan Africa inhibiting affordability. This paper therefore examines the impact of market sentiment on house prices in South Africa.

The study used the Autoregressive Distributed Lag (ARDL) approach with quarterly data spanning from 2005Q1 to 2020Q4.

In all, it was established that market sentiment plays a minimal role in the property market in South Africa. But there was enough evidence of cointegration from the bound test between sentiment and house prices. Nevertheless, the lag values of sentiment pointed to a rise in house prices. Exchange rate volatilities and inflation had a statistically significant effect on prices in both the long and short term, respectively.

Policymakers could still monitor market sentiment in the housing market due to the strong chemistry between house prices and sentiment, as evidenced from the bound test, but focus on economic fundamentals as the main policy tool for house price reduction.

The findings and the creation of the sentiment index make an invaluable contribution to the paper and add to the paucity of literature on the study of market sentiment in the housing market.

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.

This study examines green absorptive capacity as an important intervening variable that elucidates the relationship between green supply chain management (GSCM) practices (specifically, green purchasing, customer cooperation and investment recovery) and firm performance.

Drawing from the theoretical underpinnings of the natural-resource-based view theory and information processing theory, a research model is developed and tested using data obtained from 368 manufacturing firms in Ghana. Data analysis was conducted using structural equation modeling.

The results indicate that green purchasing, customer cooperation and investment recovery have a direct positive and significant effect on firm performance. Additionally, green purchasing and customer cooperation have a positive and significant effect on green absorptive capacity but investment recovery does not. Further, the results show that the paths from green purchasing and customer cooperation to firm performance are positively mediated by green absorptive capacity.

The study reveals to supply chain managers that green absorptive capacity is an important conduit through which firms can achieve enhanced firm performance from GSCM initiatives.

This study makes a contribution by integrating the absorptive capacity literature and green management literature and establishes green absorptive capacity as a mechanism through which GSCM practices enhance firm performance.

The primary aim of this paper is to concurrently use the data types to enhance econometric analysis in the housing market in developing countries, particularly Namibia.

Scholarly discussions on econometric analysis in the housing market in sub-Saharan Africa suggest that the inadequacy of time series data has impeded studies of such nature in the region. Hence, this paper aims to comparatively analyse the impact of economic fundamentals on house prices in Namibia using real and interpolated data from 1990 to 2021 supported by the ARDL model.

It was discovered that in all the three types of data house prices were affected by fundamentals except real GDP in the long term. It was also noted that there were not much significant variations between the real data and the interpolated data frequencies. However, the results of the annual data and the semi-annual interpolated data were more analogously comparable to the quarterly interpolated data

It is suggested that the adoption of interpolated data frequency type should be based on the statistical significance of the result. In addition, the need to monitor the nexus of the housing market and fundamentals is necessary for stable and sustainable housing market for enhanced policy direction and prudent property investment decision.

The study pioneer to concurrently use the data types to enhance econometric analysis in the housing market in developing countries.

This paper provides a structural model to value startup companies and determine the optimal level of research and development (R&D) spending by these companies.

This paper describes a new variant of float-the-money options, which can act as a financial instrument for financing R&D expenses for a specific time horizon or development stage, allowing the investor to share in the startup's value appreciation over that duration. Another innovation of this paper is that it develops a structural model for evaluating optimal level of R&D spending over a given time horizon. The paper deploys the Gompertz-Cox model for the R&D project outcomes, which facilitates investigation of how increased level of R&D input can enhance the company's value growth.

The author first introduces a time-varying drift term into standard Black-Scholes model to account for the varying growth rates of the startup at different stages, and the author interprets venture capital's investment in the startup as a “float-the-money” option. The author then incorporates the probabilities of startup failures at multiple stages into their financial valuation. The author gets a closed-form pricing formula for the contingent option of value appreciation. Finally, the author utilizes Cox proportional hazards model to analyze the optimal level of R&D input that maximizes the return on investment.

The integrated contingent claims model links the change in the financial valuation of startups with the incremental R&D spending. The Gompertz-Cox contingency model for R&D success rate is used to quantify the optimal level of R&D input. This model assumption may be simplistic, but nevertheless illustrative.

Once supplemented with actual transaction data, the model can serve as a reference benchmark valuation of new project deals and previously invested projects seeking exit.

The integrated structural model can potentially have much wider applications beyond valuation of startup companies. For instance, in valuing a company's risk management, the level of R&D spending in the model can be replaced by the company's budget for risk management. As another promising application, in evaluating a country's economic growth rate in the face of rising climate risks, the level of R&D spending in this paper can be replaced by a country's investment in addressing climate risks.

This paper is the first to develop an integrated valuation model for startups by combining the real-world R&D project contingencies with risk-neutral valuation of the potential payoffs.

This paper aims to center the experiences of three cohorts (n = 40) of Black high school students who participated in a critical race technology course that exposed anti-blackness as the organizing logic and default setting of digital and artificially intelligent technology. This paper centers the voices, experiences and technological innovations of the students, and in doing so, introduces a new type of digital literacy: critical race algorithmic literacy.

Data for this study include student interviews (called “talk backs”), journal reflections and final technology presentations.

Broadly, the data suggests that critical race algorithmic literacies prepare Black students to critically read the algorithmic word (e.g. data, code, machine learning models, etc.) so that they can not only resist and survive, but also rebuild and reimagine the algorithmic world.

While critical race media literacy draws upon critical race theory in education – a theorization of race, and a critique of white supremacy and multiculturalism in schools – critical race algorithmic literacy is rooted in critical race technology theory, which is a theorization of blackness as a technology and a critique of algorithmic anti-blackness as the organizing logic of schools and AI systems.