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This study aims to investigate whether managerial short-termism affects the expected default probability for a sample of Chinese-listed firms.

To capture default, we utilize the expected default probability measure developed by Bharath and Shumway (2008). Textual analysis and machine learning techniques are used to construct the index of managerial myopia. We conduct ordinary least squares regression and employ a large sample of 33,164 firm-year observations from Chinese A-share listed firms spanning the years 2001–2021 to test our theoretical hypotheses. We further conduct mediation tests, moderating analysis, textual features analysis and analysis of actual default firms. In addition, we employ change regression, entropy-balanced/propensity score/closest assets matching analysis, two-stage least squares regression, two-stage residual intervention method and alternative estimation methods to address endogeneity concerns.

First, there is a positive and statistically significant relationship between managerial myopia and expected default probability. Second, the mediation tests indicate that managerial myopia increases the expected default probability through operational risk and opportunistic agency channels. Third, the cross-sectional tests reveal that the positive association is less pronounced for firms with effective internal control systems, higher audit quality and more financial analyst coverage.

Our study reveals the need for comprehensive early warning mechanisms in the corporate bond market in China, in particular, through enhanced transparency of managerial incentive schemes and more rigorous disclosure requirements regarding short-term managerial decision-making. Furthermore, the findings of our study suggest the necessity of taking an integrated approach in developing regulatory frameworks that enable market intermediaries – including rating agencies, financial analysts and external auditors – to execute their monitoring functions with greater effectiveness.

Prior research has examined the impact of managers’ demographic characteristics on a range of corporate organizational outcomes; however, there have been few studies investigating the influence of managerial myopia on corporate financial risks. This study advances the literature on the determinants of default probability. It contributes to the limited and emerging studies on the role of managerial myopia by being the first to examine the effect of managerial myopia on expected default probability.

Maritime transportation plays an important role in facilitating both the global and regional merchandise trade, where accurate trend prediction is crucial in assisting decision-making in the industry. This paper aims to conduct a macro-level study to predict world vessel supply and demand.

The automatic autoregressive integrated moving average (ARIMA) is used for the univariate vessel supply and demand time-series forecasting based on the data records from 1980 to 2021.

For the future projection of the demand side, the predicted outcomes for total vessel demand and world dry cargo vessel demand until 2030 indicate upward trends. For the supply side, the predominant upward trends for world total vessel supply, oil tanker vessel supply, container vessel supply and other types of vessel supply are captured. The world bulk carrier vessel supply prediction results indicate an initial upward trend, followed by a slight decline, while the forecasted world general cargo vessel supply values remain relatively stable. By comparing the predicted percentage change rates, there is a gradual convergence between demand and supply change rates in the near future. We also find that the impact of the COVID-19 pandemic on the time-series prediction results is not statistically significant.

The results can provide policy implications in strategic planning and operation to various stakeholders in the shipping industry for vessel building, scrapping and deployment.

Small and medium-sized contractors are critical to micro and macroeconomic performance. These contractors in South Africa have long been confronted with the problem of business failure because of a plethora of factors, including poor productivity. The purpose of this study is to investigate salient issues undermining the productivity of small and medium-sized contractors in South Africa. This study proposes alternative possibilities to engender productivity improvement.

Qualitative data were collected using semi-structured interviews with 15 contractors in Gauteng Province, South Africa. The research data were analysed using content and causal layered analyses.

Challenges to contractors’ productivity were associated with inadequately skilled workers, management competence and political factors. Skills development, construction business and political factors were dominant stakeholders’ perceptions. Metaphors for construction labour productivity are presented and reconstructed as alternative directions for productivity improvement.

Contractors lose a substantial amount of South African Rand to poor productivity. Alternative directions provided in this study can be leveraged to increase profitability in construction organizations, enhance the social well-being of South Africans and ultimately improve the contribution of contractors to the South African economy.

The causal layered analysis (CLA) applied in this study is novel to construction labour productivity research. The four connected layers of CLA, which make a greater depth of inquiry possible, were explored to investigate labour productivity in construction organizations.