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Our result of this paper aims to indicate that the beta pricing formula could be applied in a long-term model setting as well.

In this paper, we show that the capital asset pricing model can be derived from a three-period general equilibrium model.

We show that our extended model yields a Pareto efficient outcome.

The capital asset pricing model (CAPM) model can be used for pricing long-lived assets.

Long-term modelling and sustainability can be modelled in our setting.

Our results were only known for two periods. The extension to 3 periods opens up a large scope of applicational possibilities in asset pricing, behavioural analysis and long-term efficiency.

This study examines how local governments and enterprises can implement ecological restoration of abandoned mines based on ecology-oriented development (EOD), which will be more beneficial to local environmental protection and economic development under the central government’s policy of outcome incentives or process subsidies.

We construct a dynamic differential game model to simulate the interactions between local governments and enterprises during the ecological restoration of abandoned mines from an EOD perspective.

The findings suggest that under the central government’s outcome incentive policy, cooperation between local governments and enterprises is an optimal strategy. Under the process subsidy policy, while neither cooperative nor non-cooperative models significantly affect the investment levels of local governments and enterprises, a cooperative approach ensures optimal investments from both without solely relying on the process subsidy. Additionally, incorporating altruistic preferences can lead to Pareto improvements in economic and environmental results under central government outcome incentives.

This research offers a policy foundation for governments to encourage the EOD model in the ecological restoration of abandoned mines. It provides theoretical support for achieving environmental sustainability and high-quality economic development, and is particularly significant for resource-depleted cities seeking to transform their development strategies.

Through a dynamic differential game model involving government agencies and enterprises to simulate decision-making in the ecological restoration of abandoned mines, incorporating altruistic preferences into this restoration process, and identifying optimal strategies and policies for ecological restoration.

Many industries use non-Newtonian ternary hybrid nanofluids (THNF) because of how well they control rheological and heat transport. This being the case, this paper aims to numerically study the Casson-Williamson THNF flow over a yawed cylinder, considering the effects of several slips and an inclined magnetic field. The THNF comprises Al₂O₃-TiO₂-SiO₂ nanoparticles because they improve heat transmission due to large thermal conductivity.

Applying suitable nonsimilarity variables transforms the coupled highly dimensional nonlinear partial differential equations (PDEs) into a system of nondimensional PDEs. To accomplish the goal of achieving the solution, an implicit finite difference approach is used in conjunction with Quasilinearization. With the assistance of a script written in MATLAB, the numerical results and the graphical representation of those solutions were ascertained.

As the Casson parameter β increases, there is an improvement in the velocity profiles in both chord and span orientations, while the gradients Re1/2Cf, Re1/2C¯f reduce for the same variations of β. The velocities of Casson THNF are greater than those of Casson-Williamson THNF. Approximately, a 202% and a 32% ascension are remarked in the magnitudes of Re1/2Cf and Re1/2C¯f for Casson-Williamson THNF than the Casson THNF only. When velocity slip attribute S1 jumps to 1 from 0.5, magnitude of both F(ξ,η) and Re1/2Cf fell down and it is reflected to be 396% at ξ=1, Wi=1 and β=1. An augmentation in thermal jump results in advanced fluid temperature and lower Re−1/2Nu. In particular, about 159% of down drift is detected when S2 taking 1.

There is no existing research on the effects of Casson-Williamson THNF flow over a yawed cylinder with multiple slips and an angled magnetic field, according to the literature.

The role played by corporate governance mechanisms on corporate deleveraging policies has not been clarified. Empirical evidence is confined to developed economies, even with conflicting and inconclusive results. This paper aims to examine the role of corporate governance mechanisms, such as ownership structure, board composition and CEO dominance, in explaining corporate deleveraging policies.

Using a sample of listed Pakistani firms between 2010 and 2022, this study resorts to binary response models to examine the effects of governance mechanisms on firms’ decision to go debt-free.

A greater ownership concentration, institutional ownership and family ownership increase the propensity for zero leverage. Board gender diversity decreases the propensity for deleveraging policies, which seems to indicate that the presence of females reinforces the monitoring function of the board. Finally, lower managerial ownership or CEO dominance decreases the propensity toward zero leverage (interest convergence hypothesis), but higher managerial ownership or CEO dominance increases the propensity toward zero leverage (managerial entrenchment hypothesis).

Risk-averse managers who prefer to control a firm using little or no debt will find it easier to implement these financing policies in firms with greater ownership concentration and where institutional holders have a substantial stake. For shareholders, this study suggests that investing in firms with females on board reduces the risk of corporate deleveraging policies being adopted for entrenched reasons.

The presence of females on board seems to decrease the propensity of managers to adopt opportunistic actions and may also contribute to enhancing human welfare and society in developing countries.

To the best of the authors’ knowledge, this is the first study considering the effect of board diversity on zero leverage. Another singularity is that this study exhibits a nonlinear relationship between managerial ownership and corporate deleveraging policy.

This paper analyses how firm births and deaths are influenced by previous firm births and deaths in related and unrelated sectors. Competition and multiplier effects are used as the theoretical lens for this analysis.

This paper uses 2008–2016 Irish business demography data pertaining to 568 NACE 4-digit sectors within 20 NACE 1-digit industries across 34 Irish county and sub-county regions within 8 NUTS3 regions. A three-stage least squares (3SLS) estimation is used to analyse the impact of past firm deaths (births) on future firm births (deaths). The effect of relatedness on firm interrelationships is explicitly modelled and captured.

Findings indicate that the multiplier effect operates mostly through related sectors, while the competition effect operates mostly through unrelated sectors.

This paper's findings show that firm interrelationships are significantly influenced by the degree of relatedness between firms. The raw data used to calculate firm birth and death rates in this analysis are count data. Each new firm is measured the same as another regardless of differing features like size. Some research has shown that smaller firms have a greater propensity to create entrepreneurs (Parker, 2009). Thus, it is possible that the death of differently sized firms may contribute differently to multiplier effects where births induce further births. Future research could seek to examine this.

These findings have implications for policy initiatives concerned with increasing entrepreneurship. Some express concerns that public investment into entrepreneurship can lead to “crowding out” effects (Cumming and Johan, 2019), meaning that public investment into entrepreneurship could displace or reduce private investment into entrepreneurship (Audretsch and Fiedler, 2023; Zikou et al., 2017). This study’s findings indicate that using public investment to increase firm births could increase future firm births in related and unrelated sectors. However, more negative “crowding out” effects may also occur in unrelated sectors, meaning that public investment which stimulates firm births in a certain sector could induce firm deaths and crowd out entrepreneurship in unrelated sectors.

This paper is the first in the literature to explicitly account for the role of relatedness in firm interrelationships.

The recruitment of undergraduate students within English universities is of vital importance to both the academic success and the financial stability of the organisation. Despite the primacy of the task, there has been a dearth of research looking at related performance and how to ensure that the process is optimised. The purpose of this study was to investigate the degree of variation both within a university and between different universities. The reliance that individual programmes and/or universities place on the Clearing process is key; given its uncertainty, resource demands and timing shortly before students take up their places.

The Nomogramma di Gandy diagrammatical approach utilises readily available data to analyse universities’ performance in recruiting students to different programmes, and the degree to which they each rely of the Clearing process. Inter-university performance was investigated on a whole-student intake basis for a sample of English universities, representative of type and region.

The study found that there were disparate patterns for the many programmes within the pilot university and also disparate patterns between different types of universities across England. Accordingly, universities should internally benchmark their programmes to inform both strategic and tactical decision-making. Similarly, Universities and Colleges Admissions Service benchmarking inter-university patterns could inform the overall sector.

The approach and findings provide lessons for analysing student recruitment which could be critical to universities’ academic and financial health, in an increasingly competitive environment.

The purpose of this study is to investigate the interplay between fiscal dominance and monetary policy in South Africa from 1960 to 2023.

The study employs a structural vector autoregression (SVAR) medel to analyze the relationship between fiscal dominance and monetary policy. Short-term and long-term shocks of government borrowing and deficits are examined to understand their impact on inflation dynamics.

Fiscal dominance has a significant effect both in the short and long run. There is evidence that government debt and deficits increase inflation, overriding the effects of monetary policy aimed at maintaining price stability. On the other hand, the study reveals that money supply shocks have a greater effect in reducing fiscal dominance compared to interest rate shocks. The variance movement on inflation is significantly explained by government debt and deficits. This emphasizes the persistence of inflationary pressures associated with fiscal dominance, highlighting the importance of effective policy interventions to mitigate inflationary risks.

This study contributes to the existing literature by providing insights into the dynamics of fiscal dominance in South Africa. Moreover, this study extends the theoretical framework of the fiscal theory of the price level (FTPL) and the government budget constraint. This study contributes valuable insights into the dynamics of fiscal dominance in South Africa and offers guidance for policymakers in formulating strategies to safeguard economic stability.

This study aims to introduce an innovative approach to predictive maintenance by integrating time-series sensor data with event logs, leveraging the synergistic potential of deep learning models. The primary goal is to enhance the accuracy of equipment failure predictions, thereby minimizing operational downtime.

The methodology uses a dual-model architecture, combining the patch time series transformer (PatchTST) model for analyzing time-series sensor data and bidirectional encoder representations from transformers for processing textual event log data. Two distinct fusion strategies, namely, early and late fusion, are explored to integrate these data sources effectively. The early fusion approach merges data at the initial stages of processing, while late fusion combines model outputs toward the end. This research conducts thorough experiments using real-world data from wind turbines to validate the approach.

The results demonstrate a significant improvement in fault prediction accuracy, with early fusion strategies outperforming traditional methods by 2.6% to 16.9%. Late fusion strategies, while more stable, underscore the benefit of integrating diverse data types for predictive maintenance. The study provides empirical evidence of the superiority of the fusion-based methodology over singular data source approaches.

This research is distinguished by its novel fusion-based approach to predictive maintenance, marking a departure from conventional single-source data analysis methods. By incorporating both time-series sensor data and textual event logs, the study unveils a comprehensive and effective strategy for fault prediction, paving the way for future advancements in the field.

Visual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment.

This paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model.

The various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks.

Compared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.

We are the first to investigate the relationship between seasoned equity offerings (SEOs) and anchoring on historical high prices in China.

We use the ratio of the recent closing price to its historical high in the previous 12–60 months (anchoring-high-price ratio) to study its impact on the market timing of SEOs.

Empirical results show that the anchoring-high-price ratio significantly and positively affects the probability of additional stock issuances. Contrary to the USA market, the Chinese stock market reacts negatively to the SEOs at historical highs. Moreover, the anchoring-high-price ratio exacerbates the negative effect of announcements and leads to long-term underperformance. Finally, we investigate the impact of the anchoring-high-price ratio on a company’s capital structure, showing that the additional issuance anchoring on historical highs reduces the company’s leverage ratio in the long run. Overall, our findings support the anchoring theory and can help understand better the anchoring behavior of managers and the company’s decision on additional stock issuances.

We are the first to use the anchoring-high-price ratio to study the timing of SEOs. We find that the anchoring-high-price ratio positively affects the probability of SEOs. Unlike the USA, the Chinese stock market reacts negatively to SEOs at high prices. SEOs anchoring on historical highs reduce a firm’s leverage ratio in the long run. Finally, our results support the anchoring theory.