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This paper investigates the impact of institutional factors on financial deepening and its implications on bank credit in Africa.

The paper employs different panel econometric models to examine the heterogeneity of 50 African countries from 2000 to 2019. The estimators include panel corrected standard errors, system generalized method of moments, quantile and threshold regressions.

The results show that rule of law, regulatory quality, government effectiveness, voice and accountability, control of corruption and political stability significantly influence financial deepening in Africa. However, government effectiveness has a higher effect on middle- and high-income countries, while other indicators have a high impact on low-income countries. All institutional indicators have stronger effects, almost double, at higher financial depth levels than for countries with lower levels. Government effectiveness and regulatory quality impact financial deepening more for countries with strong institutions than weak ones. Thus, the relationship between institutional qualities and credit provided by banks is non-monotonic.

The findings suggest that strengthening appropriate institutional factors based on country heterogeneity may effectively stimulate debt financing in Africa, the primary source of financing for small and medium-sized enterprises and entrepreneurs.

The novelty of this paper is that previous studies did not sufficiently scrutinize the heterogeneity of the structure of African economies – i.e. differences in institution, credit and income levels.

This paper aims to show that information asymmetry plays a vital role in the post-M&A performance-time until deal completion nexus. The findings are that the due diligence hypothesis and the overdue hypothesis proposed and tested in Thompson and Kim (2020) are influenced by the information asymmetry of the target during the negotiation process. Thus, mergers that involve more opaque targets that take a shorter time to close perform better, whereas those that take too long to close experience poor post-M&A performance. Conversely, there is no such effect when the mergers involve targets that are transparent and not plagued with large information asymmetry problems. These results hold for the short-term supporting the evidence that information asymmetry problems are severe before the merger is consummated and become attenuated post-merger.

This study aims to form a new concept of power-to-gas-based virtual power plant (GVPP) and propose a low-carbon economic scheduling optimization model for GVPP considering carbon emission trading.

In view of the strong uncertainty of wind power and photovoltaic power generation in GVPP, the information gap decision theory (IGDT) is used to measure the uncertainty tolerance threshold under different expected target deviations of the decision-makers. To verify the feasibility and effectiveness of the proposed model, nine-node energy hub was selected as the simulation system.

GVPP can coordinate and optimize the output of electricity-to-gas and gas turbines according to the difference in gas and electricity prices in the electricity market and the natural gas market at different times. The IGDT method can be used to describe the impact of wind and solar uncertainty in GVPP. Carbon emission rights trading can increase the operating space of power to gas (P2G) and reduce the operating cost of GVPP.

This study considers the electrical conversion and spatio-temporal calming characteristics of P2G, integrates it with VPP into GVPP and uses the IGDT method to describe the impact of wind and solar uncertainty and then proposes a GVPP near-zero carbon random scheduling optimization model based on IGDT.

This study designed a novel structure of the GVPP integrating P2G, gas storage device into the VPP and proposed a basic near-zero carbon scheduling optimization model for GVPP under the optimization goal of minimizing operating costs. At last, this study constructed a stochastic scheduling optimization model for GVPP.

The study introduces a new approach to leverage-value relationship. Besides applying the classical regression models, the study deals with leverage as a continuous treatment variable implemented on the firm’s value using the dose-response function (DFR).

After proper model calibration and splitting the treatment (leverage) into ten doses, a response function is generated, which enables the realization of the dose level at which the firm’s value is maximized. Furthermore, the study tests the pecking order theory (POT) and the trade-off theory (TOT) using the threshold model to see whether firms are under or over-indebted. The analysis is carried out on panel data from small-medium enterprises (SMEs), providing more valuable insights than large and mature companies.

The study used two leverage measures: total liabilities ratio and bank debt ratio. Value is measured by the market capitalization and Tobin’s Q. In general, the study finds a positive relationship between leverage and value; POT is not strongly supported, firms are below their optimal leverage and there is a certain leverage dose that would maximize firms’ value.

Since the threshold model and DRF show that SMEs are under-indebted, firms could benefit from extra leverage doses without affecting the firm’s risk profile, especially in a low-interest rate regime, and the potential increase in public-private expenditure after Italy obtained the European Recovery Funds.

The study contributes to new knowledge and understanding of financial leverage from new methodological perspectives, offering valuable insights from SMEs using novel approaches.

Corporate real estate management (CREM) is complex due to an increasing number of real estate (RE) added values and the tensions between them. RE managers are faced with trade-offs: to choose a higher performance for one added value at the cost of another. CREM research mainly deals with trade-offs in a hypothetical sense, without looking at the characteristics of the RE portfolio nor the specific context in which trade-offs are made. The purpose of this paper is to further develop the concept of real estate value (REV) optimisation with regard to tensions between decreasing CO₂ emissions and supporting user activities.

Mixed method study. REV optimisation between user activities and energy efficiency for police stations in the Netherlands built between 2000 and 2020 is analysed. This is complemented by interviews with an RE manager and senior user of police stations and analysis of policy documents.

The characteristics of the police station portfolio indicate no correlation between user activities and energy efficiency for the case studied. This is complemented by interviews, from which it becomes clear that there was in fact little tension between supporting user activities and energy efficiency. The performances of these two different added values were optimised separately.

This study combines different scales (building and portfolio level) with different types of data: portfolio analysis, document analysis and interviews. This creates a comprehensive image of whether and how the Netherlands police optimised the two RE values.

This paper aims to investigate the possible non-linear effect of net working capital (NWC) level on profitability for Middle East and North Africa (MENA) region listed companies. Furthermore, the study tests the possible interactive effect of cash levels on the relationship between NWC and profitability.

NWC level is the independent variable and profitability is the dependent variable using two proxies, return on assets (ROA) and returns on equity (ROE). Control variables are size, leverage, gross domestic product growth and sales revenue growth. The generalized method of moments was used to analyze the data of 134 consumer-goods listed firms in 12 MENA countries for the period 2013–2019.

The results demonstrate that NWC levels had a non-linear effect on profitability using ROA as a profitability proxy while results were insignificant using ROE as a profitability proxy. Furthermore, results show the absence of interactive effects between NWC, cash levels and both profitability proxies.

The study fills a gap in the working capital management (WCM) literature by providing new evidence on WCM’s non-linear effect of corporate performance in the MENA region emerging markets using the consumer-goods industry sample. The study contributes to the financial managers’ working capital optimization efforts in the MENA region by providing evidence on the usefulness of WC optimization efforts in the region from a financial performance point of view. According to the researchers’ knowledge, a few studies attempted to investigate this non-linear relationship for neither MENA region countries nor the consumer-goods industry.