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This paper aims to investigate the association between negative tone in annual report narratives and future performance in the UK context. Under the principle-based approach in the UK, managers tend to bias the tone of narrative reports upward, as the reporting regime is more flexible than the rule-based approach in the USA. Consequently, any negative disclosure not mandated by regulators conveys credible information about a firm’s prospects.

This paper uses a sample of UK FTSE all-share non-financial companies from 2010 to 2019. The authors use the textual-analysis approach based on Loughran and McDonald (2011)’s wordlist (LM) to measure the negative tone in UK annual reports.

The results show a significant negative association between negative tone and future performance. Moreover, our further analyses suggest that only the negativity in the executive section of the annual disclosures correlates significantly with future performance. In summary, this study suggests that negativity does matter under the principle-based approach and can be used as an indicator of future performance.

In contrast to the literature arguing that only positivity has the power to affect a firm’s outcomes under the principle-based approach, the authors provide new empirical evidence suggesting that negativity also matters within the UK context and can be used as an indicator for future performance. Also, to the best of the authors’ knowledge, this is the first study to identify which section of the annual report is more informative about a firm’s future performance.

This paper analyzes the direct effect of financial development and the mediating impact of financial development through foreign direct investment (FDI), foreign aid and trade on economic growth for all Asian countries.

A fixed-effect model with Driscoll–Kraay panel corrected estimators was employed to find the direct and mediating impact of financial developments on growth for all 47 Asian economies from 1980 to 2020. The bootstrapped panel-quantile regression (BPQR) model is used to check how this effect varies for different income groups of countries.

The results demonstrated that financial development positively impacts countries' economic growth. The interaction effect of financial development with FDI, foreign aid and foreign trade negatively impacts economic growth. The BPQR results showed that FDI and foreign aid help in the growth of lower quantile economies; however, the impact is negative for middle- and upper-income countries. Trade impacts growth positively for all the quantiles of economies.

The results suggest that the Asian economies must continue to provide thrust on the financial development of their own countries to achieve better growth. It also implied that the dependence on external finance is good for low-income countries and not advisable for middle- and upper-income countries.

To the best of the authors’ knowledge, the current study is the first to provide empirical evidence on analyzing both the direct and interaction effect of financial development on economic growth by considering all the Asian economies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2022-0587

The study examines the impact of fiscal policy shocks on economic growth and income inequality in Ghana. This has become necessary because of the interdependence between growth and income inequality and the role fiscal policy plays in this relationship in the development process of a country. Thus, a study that investigates how government expenditure shock and tax revenue shock influence the relationship between economic growth and income inequality could assist policymakers to adopt the best policy mix to ensure income equity and sustained economic growth in Ghana.

It employs sacrifice ratio from structural VAR model using quarterly time series data from 1996 to 2019 on Ghana.

Our results show that government expenditure shock impacts economic growth, exchange rate and education positively and significantly in the long run. Also, tax revenue shock has a positive impact on income inequality, economic growth and education. The findings further show that there exists a trade-off between economic growth and income inequality in the long run.

The relationships between fiscal policy shocks, economic growth and income inequality have been extensively discussed among scholars. Understanding how these three macroeconomic variables are determined and their interrelationships are crucial for policymakers. This is because fiscal policy aids in both economic growth and income inequality. In the empirical literature, the emphasis has been on independently estimating the growth effects of fiscal policy or the distribution effects of fiscal policy, leaving out the existence of possible trade-off between economic growth and income inequality following a fiscal shock. To the best of our knowledge, no empirical study has been done on Ghana to empirically examine the trade-off between economic growth and income inequality as we do in this paper.

This research aims to develop an automated and optimization algorithms (OAs)-integrated 4D building information modeling (BIM) approach and a prototype and enable construction managers and practitioners to estimate the time of compound elements in building projects using the resource specification technique.

A 4D BIM estimation process was first developed by applying the resource specification and geometric information from the BIM model. A suite of OA including particle swarm optimization, ant colony, differential evolution and genetic algorithm were developed and compared in order to facilitate and automate the estimation process. The developed processes and porotypes were linked and integrated.

The OA-based automated 4D BIM estimation prototype was developed and validated through a real-life construction project. Different OAs were applied and compared, and the genetic algorithm was found as the best performing one. The prototype was successfully linked with BIM timeliner application. By using this approach, the start and finish dates of all object-based activities are developed, and the project completion time is automatically estimated.

Unlike conventional construction estimation methods which need various tools and are error prone and time-consuming, the developed method bypasses the existing time estimation tools and provides the integrated and automated process with BIM and machine learning algorithms. Furthermore, this approach integrates 4D BIM applications into construction design procedures, connected with OA automation.

This study forecasts the government expenditure components in Nigeria, including recurrent and capital expenditures for 2021 and 2022, based on data from 1981 to 2020.

The study employs statistical/econometric problems using the Feasible Quasi Generalized Least Squares approach. Expenditure forecasts involve three simulation scenarios: (1) do nothing where the economy follows its natural path; (2) an optimistic scenario, where the economy grows by specific percentages and (3) a pessimistic scenario that defines specific economic contractions.

The estimation model is informed by Wagner's law specifying a positive link between economic activities and public spending. Model estimation affirms the expected positive relationship and is relevant for generating forecasts. The out-of-sample results show that a higher proportion of the total government expenditure (7.6% in 2021 and 15.6% in 2022) is required to achieve a predefined growth target (5%).

This study offers empirical evidence that specifically requires Nigeria to invest a ratio of 3 to 1 or more in capital expenditure to recurrent expenditure for the economy to be guided on growth.

Driven by the Sustainable Development Goals (goals 7, 8, 12 and 13), this study investigates the moderating role of financial development in the link between energy poverty and a sustainable environment in African nations.

Panel cointegration analysis, fully modified least squares, Driscoll and Kraay least squares and method of moments quantile regression were used as estimation techniques to examine the link between financial development, energy poverty and sustainable environment for 28 African nations. Energy poverty is measured using two proxies-access to clean energy and access to electricity, while the environment is gauged using ecological footprint.

The regression outcomes show that access to clean energy and electricity negatively impacts the ecological footprint across all the quantiles; hence, energy poverty increases environmental degradation. Financial development positively influences environmental degradation in the region at the upper quantiles. Similarly, the interactive term of energy poverty and financial development has a significant positive impact on ecological footprint; thus, the financial sector adds to energy poverty and environmental degradation. The results of other variables hint that per capita income and institutions worsen environmental quality while urbanisation strengthens the environment.

This study offers fresh insights into the moderating effect of financial development in the link between energy poverty and sustainable environment in African countries.

Open innovation (OI), by now one of the major concepts for the analysis of innovation, is seen as a methodology for collaboratively designing and implementing solutions by engaging stakeholders in an iterative and inclusive service design process. This paper aims to empirically investigate OI capacities, defined as a cooperative, knowledge-sharing innovation ecosystem, and to explore how it can lead to improved performance of firms in Central and Eastern European (CEE) and Southeastern European (SEE) countries.

The study builds on the World Bank/European Bank for Reconstruction and Development (EBRD’s) Business Environment Enterprise Performance Survey (BEEPS) dataset for 2009, 2013 and 2019. Primarily, the research model was estimated using log-transformed ordinary least squares (OLS). Taking into consideration that this method might produce substantial bias, yielding misleading inferences, this study is fitting Poisson pseudo maximum likelihood estimators with robust standard errors and instrumental variable/generalized method of moments estimation (IV/GMM) approach for comparative results. Secondarily, the research model was tested using structural equation modelling (SEM) to investigate the relationship between five OI capacities and firm performance.

The findings indicate that there is a significant positive relationship between most OI capacities and firm performance, except for innovation, which did not show a statistically significant relationship with firm performance. Specifically, research and development (R&D), knowledge and coopetition are statistically significant and positively associated with firm performance, whereas transformation is statistically significant but negatively associated with firm performance. The IV/GMM estimations’ findings support the view that the firm performance is significantly affected by OI capacities, together with some control variables such as size, age, foreign ownership and year dummy to have a significant impact on firm performance.

This paper fills an identified gap in the literature by investigating the impact of OI on firm performance executed in the specific CEE and SEE country context.

The study examines the effect of natural resources (NRs) and the control of corruption, voice and accountability and regulatory quality on carbon emissions in Africa. Aside from their individual effects, the moderation effect of institutional quality is assessed.

Data from 32 African countries from 2002 to 2021 and the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) regression methods were used for the investigation.

In the long term, the NRs effect is sensitive to the estimation technique employed. However, quality regulatory framework, robust corruption control and voice and accountability abate any positive effect of NRs on carbon emissions. Institutional quality can be argued to moderate the CO2-emitting potentials of resource extraction in the selected African countries.

Enhancing regulation quality, enforcing corruption control and empowering citizens towards greater participation in governance and demanding accountability are essential catalyst to effectively mitigate CO2 emissions resulting from NRs.

The moderation effect of control of corruption, voice and accountability and regulatory quality on the NR–carbon emission nexus is examined.

Despite the importance of tax policy in reducing energy consumption and carbon emissions, there is a dearth of research on the environmental impact of indirect taxes. This paper examines the impact of indirect taxes on carbon dioxide (CO₂) emissions, with an emphasis on institutional quality.

The study uses the Government Revenue Dataset (2021), comprising 143 countries, dividing into 114 developing and 29 developed countries, during the period between 1996 and 2019. The author adopts panel data techniques, with Driscoll–Kraay standard errors to account for the issue of cross-sectional dependence (CSD).

The results indicate that indirect tax revenues have a negative and significant impact on CO₂ emissions for the total sample. The subsample analysis revealed that while indirect taxes reduce carbon emissions in developing countries, opposed results are reported for developed countries. This finding implies that most of the advanced countries have already reached a high level of taxes, at which carbon emissions increase as indirect tax increases further. Interestingly, the results revealed that institutional quality enhances the role of indirect taxes in mitigating carbon emissions for both developing and developed countries.

To the best of the authors' knowledge, this is the sole study using the newly developed tax data by the United Nations University, World Institute for Development Research (UNU-WIDER) to investigate the impact of indirect taxes on carbon emissions, with an emphasis on institutional quality. The existing literature focuses on specific taxes, like carbon taxes, with no comprehensive research on the link between indirect taxes and carbon emissions.

This analysis examines the relationship between corruption and firm productivity in Vietnam.

The authors apply the system generalized method of moments estimation approach on a panel dataset constructed from comprehensive enterprise surveys covering all the sectors over the 2011–2020 period.

The results confirm a non-linear relationship between corruption and firm productivity. Where corruption is severe, leaving corruption alone tends to benefit firm productivity because efforts to control corruption are likely to cause greater delays. In less corrupt provinces, corruption appears to harm firm productivity while efforts to control corruption provide significant productivity gains. This U-shaped relationship is confirmed for small firms and those in the private sector sub-samples. Intriguingly, this study reveals that the U-shaped relationship does not apply to micro, medium, large firms, state-owned firms and foreign-invested firms because corruption is found to have no significant impact on productivity among these sub-samples. Changes in regulations after 2014 toward promoting a transparent business environment are shown to foster the positive impact of lowering corruption on firm productivity.

This study suggests that lowering corruption is beneficial for firm productivity at the micro level. However, where corruption is severe, monitoring corruption alone is likely to cause adverse effects on productivity due to increased bureaucratic delays. Institutional reforms might play an important role in leveraging the effects of lowering corruption on productivity in highly corrupt areas.

This paper sheds new light on the relationship between corruption and firm productivity in the broad existing literature and especially in the limited number of studies for Vietnam.