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This study examines the impacts of the Ethiopian developmental state model on the competition, efficiency and profitability of banks.

The competition, efficiency and profitability of the Ethiopian bank are measured using Panzar Rose, data envelopment analysis and financial ratio. Fixed-effect panel regression methods are applied to test the direction and strength of association between the Ethiopian developmental state model and the competition, efficiency and profitability of the country's banks while controlling bank-specific market structure and macroeconomic factors.

The Ethiopian developmental state model embeds the state-directed financial system, which affects the banking industry using a range of credit allocation instruments. Of which, directed credit schemes, interest rate control and the lack of financial freedom reduce the competition and efficiency of banks. The National Bank of Ethiopia (NBE) advances to the government and the sale of Treasury bills to a captive market enhances banking competition while negatively affecting banking efficiency. Interest rate control and the lack of financial freedom lower banking profitability. Unexpectedly, directed credit schemes improve banking profitability.

As with any study, this one has limitations. The intra-period comparison of efficiency is based on balanced data. Future studies can use methods that can measure the efficiency of banks using unbalanced data. The computation of the yearly H-statistic is constrained by the small sample size. The use of high-frequency data for measuring competition can provide us with better insights into banking competition in Ethiopia. Furthermore, there are a number of methods for measuring banking competition, efficiency and profitability with different assumptions. Approaching the subject of this study by applying different methods will offer different insights.

The contributions of this study to practice are at two levels. First, at the policy level, it enhances our understanding of the impacts of developmental state model policies, as implemented in Ethiopia, on the banking industry and therefore provides suggestions to policymakers to reform the sector's policies. Second, it offers input to the management of banks regarding the factors that impact the industry.

The banking industry is often studied in the context of financial liberalisation. The originality of this study lies in investigating how the competition, efficiency and profitability of banks are affected when operating in the context of significant state interventions in the industry.

This study is focused to support an ongoing development project of the case company's current state and the challenges of the order-to-cash (O2C) process. The O2C process is the most visible process to the customer, and therefore, its punctual and fluent order management is vital. It is observed that the high degree of manual work in the O2C process causes mistakes, delays and rework in the process. The purpose of this article is therefore to analyze the case company's current state of the O2C process as well as to identify the areas of development in this process by deploying the means of Lean Six Sigma tools such as value stream mapping (VSM).

The study was conducted as a mix of quantitative and qualitative analysis. Based on both the quantitative and qualitative data, a workshop on VSM was organized to analyze the current state of the O2C process of a case company, engaged in the energy and environment sector in Finland.

The results found that excessive manual work was highly connected to inadequate or incorrect data in pricing and invoicing activities, which resulted in canceled invoices. Canceled invoices are visible to the customer and have a negative impact on the customer experience. This study found that by improving the performance of the O2C process activities and improving communication among the internal and external stakeholders, the whole O2C process can perform more effectively and provide better customer value.

The O2C process is the most visible process to the customer and therefore its punctual and fluent order management is vital. To ensure that the O2C process is operating as desired, suitable process performance metrics need to be aligned and followed. The results gathered from the case company's data, questionnaire interviews, and the VSM workshop are all highlighted in this study. The main practical and managerial implications were to understand the real-time O2C process performance, which is necessary to ensure strong performance and enhance continuous improvement of the O2C process that leads to operational excellence and commercial competitiveness of the studied case company.

This study evaluated the effect of macroeconomic factors on residential real estate (RE) investment returns in the cities of Abuja and Lagos, Nigeria, with a view to guiding RE investors and researchers.

A survey research design was employed using a questionnaire to collect RE transaction data from 2008 to 2022 from estate surveying and valuation firms in the study areas. Rental and capital value data collected were used to construct rental and capital value indices and total returns on investment. The macroeconomic data used were retrieved from the archives of the Central Bank of Nigeria (CBN). Granger causality (GC) and multiple regression models were adopted to evaluate the effect of selected macroeconomic variables on residential RE investment returns in the study areas.

The study found a progressive upward movement in rental and capital values of residential RE investment in the study areas within the study period. Total and risk-adjusted returns on investment were equally positive within the study period. Only the inflation rate, unemployment rate and real gross domestic product (GDP) per capita were found to be the major determinants of residential RE investment returns in the study areas within the study period.

The secrecy associated with property transaction information/data by RE practitioners in the study areas posed a challenge. Property transaction data were not adequately kept in a way for easier access and retrieval in many of the estate firms and agent offices. Consequently, there was a lack of data that spanned the study period in some of the sampled estate firms or agent offices. This data collection challenge was, however, overcome by the excess time spent retrieving the required data for this study to ensure that the findings appropriately answer the research questions.

Inflation and GDP per capita have been found to be significant factors that influence residential RE investment performance in the study areas. Therefore, investors should pay attention to these identified macroeconomic factors for residential RE investment in the study areas whilst making investment decisions in order to mitigate a possible loss of income or return. The government should formulate and implement economic policies that would address the current high unemployment and inflation rates in Nigeria at large.

This study has extended and further enriched the existing body of knowledge in the field of RE investment analysis in Nigeria. To the best of the authors' knowledge, this study is the first to adopt the Cornish Fisher value-at-risk and modified Sharpe ratio models to analyse risk and risk-adjusted returns on residential RE investment, respectively, in Nigeria. It has therefore redirected the focus of RE researchers and practitioners to a more objective approach to RE investment performance analysis in Nigeria.

The aim of this paper is threefold: (1) to develop a new measure of investor sentiment rational (ISR) of developing countries by applying principal component analysis (PCA), (2) to investigate co-movements between the ten developing stock markets, the sentiment investor's, exchange rates and geopolitical risk (GPR) during Russian invasion of Ukraine in 2022, (3) to explore the key factors that might affect exchange market and capital market before and mainly during Russia–Ukraine war period.

The wavelet approach and the multivariate wavelet coherence (MWC) are applied to detect the co-movements on daily data from August 2019 to December 2022. Value-at-risk (VaR) and conditional value-at-risk (CVaR) are used to assess the systemic risks of exchange rate market and stock market return in the developing market.

Results of this study reveal (1) strong interdependence between GPR, investor sentiment rational (ISR), stock market index and exchange rate in short- and long-terms in most countries, as inferred from (WTC) analysis. (2) There is evidence of strong short-term co-movements between ISR and exchange rates, with ISR leading. (3) Multivariate coherency shows strong contributions of ISR and GPR index to stock market index and exchange rate returns. The findings signal the attractiveness of the Vietnamese dong, Malaysian ringgits and Tunisian dinar as a hedge for currency portfolios against GPR. The authors detect a positive connectedness in the short term between all pairs of the variables analyzed in most countries. (4) Both foreign exchange and equity markets are exposed to higher levels of systemic risk in the period of the Russian invasion of Ukraine.

This study provides information that supports investors, regulators and executive managers in developing countries. The impact of sentiment investor with GPR intensified the co-movements of stocks market and exchange market during 2021–2022, which overlaps with period of the Russian invasion of Ukraine.

This study aims to provide and illustrate the application of a framework for conducting techno-economic analyses (TEA) of early-stage designs for net-zero water and energy, single-family homes that meet affordable housing criteria in diverse locations.

The framework is developed and applied in a case example of a TEA of four designs for achieving net zero-water and energy in an affordable home in Saint Lucie County, Florida.

Homes built and sold at current market prices, using combinations of well versus rainwater harvesting (RWH) systems and grid-tied versus hybrid solar photovoltaic (PV) systems, can meet affordable housing criteria for moderate-income families, when 30-year fixed-rate mortgages are at 2%–3%. As rates rise to 6%, unless battery costs drop by 40% and 60%, respectively, homes using hybrid solar PV systems combined with well versus RWH systems cease to meet affordable housing criteria. For studied water and electricity usage and 6% interest rates, only well and grid-tied solar PV systems provide water and electricity at costs below current public supply prices.

This article provides a highly adaptable framework for conducting TEAs in diverse locations for designs of individual net-zero water and energy affordable homes and whole subdivisions of such homes. The framework includes a new technique for sizing storage tanks for residential RWH systems and provides a foundation for future research at the intersection of affordable housing development and residential net-zero water and energy systems design.

This study seeks to build a financial uncertainty index for Saudi Arabia. This index serves as a leading indicator of Saudi economic activity and helps to describe economic fluctuations and forecast economic trends.

This study adopts an extension of the Jurado et al. (2015) procedure by combining financial uncertainty factors with their net spillover effects on GDP and inflation to construct an aggregate financial uncertainty index. The authors consider 13 monthly financial variables for Saudi Arabia from January 2010 to June 2021.

The empirical results show that the constructed financial uncertainty estimates are good leading indicators of economic activity. The robustness analysis suggests that the authors’ proposed financial uncertainty estimators outperform the alternative estimates used by other existing approaches to estimate the financial conditions index.

To the best of the authors’ knowledge, this is the first attempt at constructing a financial uncertainty index for Saudi Arabia. This study extends the empirical literature, from which the authors propose a novel conceptual framework for building a financial uncertainty index by combining the approach of Jurado et al. (2015) and the time-varying connectedness network approach proposed by Antonakakis et al. (2020)

The board structure (BS) is pivotal in modern corporate governance (CG). This study aims to investigate BS variables (BSIZE, BIND and chief executive officer [CEO] duality) and their correlation with risk-taking behavior indicators, enriching the understanding of how CG shapes financial institutions’ (FIs) decision-making in Pakistan.

By scrutinizing data from 67 financial entities listed on the Stock Exchange of Pakistan spanning from 2011 to 2022 through panel data regression techniques, the research emphasizes that BS holds a substantial influence over the risk tendencies exhibited by these firms.

Key findings suggest that board size has a positive influence, aligned with previous CG research. Smaller boards perform better and avoid excessive risk-taking, contrasting some negative relationship claims. More independent directors are recommended to curtail risk and financial disruption. Holding both CEO and chair roles reduces risk exposure, resonating with reputational and employment risk theory. It is essential to recognize that BS’s impact on risk-taking is nuanced and context-dependent.

Policymakers, scholars, practitioners and investors working in the market for financial companies might greatly benefit from the empirical findings of this study. Imposing mandates on FIs to uphold adequate capital reserves functions as a safeguard against unforeseen losses, thereby diminishing the probability of unwarranted risk-taking.

Prior studies in this domain predominantly focus on nonfinancial sectors. In addition, existing research often explores the relationship between BS and firm risk-taking solely within the banking sector, overlooking other FIs. This study contributes by using a comprehensive data set encompassing all types of FIs, thus extending the existing literature.

In the current era of Industry 4.0, the manufacturing industries are striving toward mass production with mass customization by considering human–robot collaboration. This study aims to propose the reconfiguration of assembly systems by incorporating multiple humans with robots using a human–robot task allocation (HRTA) to enhance productivity.

A human–robot task scheduling approach has been developed by considering task suitability, resource availability and resource selection through multicriteria optimization using the Linear Regression with Optimal Point and Minimum Distance Calculation algorithm. Using line-balancing techniques, the approach estimates the optimum number of resources required for assembly tasks operating by minimum idle time.

The task allocation schedule for a case study involving a punching press was solved using human–robot collaboration, and the approach incorporated the optimum number of appropriate resources to handle different types of proportion of resources.

This proposed work integrates the task allocation by human–robot collaboration and decrease the idle time of resource by integrating optimum number of resources.