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The purpose of this paper is to investigate the relationship between CEOs' inside debt holdings (pension benefits and deferred compensation) and the operating leverage of the firms they manage, with the aim to examine whether CEO incentives play a role in corporate risk-taking.

The authors investigate the relation between CEO inside debt holdings (CIDH) (pension benefits and deferred compensation) and the operating leverage (DOL) of the firms they manage. Using a sample of 11,145 US firm-year observations over the period 2006–2017, the authors find a strong negative association between CIDH and DOL. Additional analyses reveal that the relationship between CIDH and DOL is more pronounced in firms with heightened agency issues, powerful CEOs and for CEOs with stronger professional networks. The results are robust to various sensitivity and endogeneity tests.

The authors find strong evidence confirming the expected negative association between CEO inside debt and DOL suggesting that firms with higher inside debt tend to maintain lower levels of operating leverage. These findings continue to hold with the alternative measure for the inside debt and operating leverage, and across a range of tests designed to rule out the possibility that the primary findings are in any way driven by potential endogeneity. In addition, the findings demonstrate that the presence of manager-shareholder agency conflicts can strengthen the inside debt–DOL relationship suggesting the strong role of inside debt in reducing firm risk.

Findings in this paper have implications for design of compensation structures so that corporate boards can establish incentives as a tool for risk management. A limitation of this study is that it is focused on one market, i.e. US listed companies, so the findings may not be applicable on a global scale.

To the best of the authors’ knowledge, this is the first study that links firm-level management of operating leverage through design of CEO inside debt incentives (two obvious choices for risk-reduction at the CEOs’ disposal include reducing financial risk through reduction of firm leverage and reducing operating risk through reduction of operating leverage). While use of firm leverage as an instrument of choice has been explored in the past, use of operating leverage to achieve risk reduction when CEO possess high inside holding, has received very little attention.

This study examines the effect of digitalization on poverty and income inequality in developing countries. The study answers the question of whether digitalization is a way for developing countries to get out of poverty and income inequality.

The study uses data from 17 developing countries with data from 2005 to 2021. The study employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS), with an augmented mean group (AMG) for robustness. Digitalization, as the variable of interest, is proxied by the digitalization index (DI), constructed using principal component analysis (PCA). The dependent variables are poverty and income inequality, which are used in different models.

The evidence indicates that digitalization decreases poverty and income inequality in developing countries. These findings are justified when we use the AMG estimator, but the strength of the coefficients and significance levels are higher in the FMOLS and DOLS estimators. The results of the control variables also show that human development (LHDI), CO2 emissions and foreign direct investment (FDI) have decreasing effects on poverty and income inequality. Thus, digitalization is a good option for developing countries to get out of poverty and income inequality to achieve sustainable development goals (1&10).

This study provides rigorous empirical evidence on the effect of digitalization on poverty and income inequality in developing countries. Unlike the previous studies on developing countries, this study used a DI to proxy digitalization. In addition, the authors use FMOLS and DOLS estimators, with an AMG estimator for robustness, to provide long-run coefficients.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0586

This study aims to examine the impact of oil consumption on carbon dioxide (CO₂) emissions and total factor productivity (TFP) in highly oil-consuming countries of the world from 1995 to 2019.

For this purpose, fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are applied.

FMOLS and DOLS models reveal that oil consumption, human capital, population, trade openness and nonrenewable energy have a significant positive effect on CO₂ emissions. While information and communication technology (ICT), as proxied by mobile and natural resources, has a significant negative effect on CO₂ emissions. In the case of TFP, oil consumption, ICT and natural resources have a significant positive effect on the TFP. On the other hand, trade openness, population, human capital and nonrenewable energy have a significant negative effect on TFP. The results of this study can help to provide policy recommendations to reduce CO₂ emissions in studied highly oil-consuming countries of the world.

Due to the threat to sustainable development, climate change has become a major topic for debate around the world. The influence of oil consumption on CO₂ emission and TFP is less known in the available literature. Another significance of this study is that many researchers considered aggregate energy consumption to study this relationship, but the authors have studied the effect of energy consumption, particularly from oil in the top oil-consuming countries, which is a significant shortcoming of the present research.

This study examines the impact of profitability, firm size and leverage on corporate tax avoidance in Bangladesh, an emerging South Asian economy.

A balanced panel data of 62 firms from Dhaka and Chittagong stock exchanges in Bangladesh from 2009 to 2020 were used to run the regression. This study employed the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) to examine the hypotheses.

The findings show that large firms positively impact corporate tax avoidance. Similarly, profitability and leverage are positively associated with tax avoidance, and the results are significant. Furthermore, the study conducts robustness tests that confirm the findings.

The use of cash effective tax rate (ETR) to investigate firms’ tax avoidance practices poses some limitations, and the results should be interpreted cautiously.

The current study may help policymakers better enhance tax collection from business firms. The findings could serve as a valuable input for effectively monitoring tax collection from large profit-earning firms.

To the authors' best knowledge, this is the first historical attempt in Bangladesh to use panel data to examine the relationship between the firm’s level characteristics and corporate tax avoidance. Panel data often provides greater flexibility with large data, simplifying calculation and statistical analysis.

The purpose of this study is to dissect the transport infrastructure performance, public spending in transport infrastructure development and the manufacturing sector in determining the transport sector energy consumption.

An analysis of transport energy consumption with the transport infrastructure performance, public spending in transport infrastructure and manufacturing sector output in India using annual data for the period 1987–2019. The study used the autoregressive distributed lag (ARDL) bounds test approach along with FMOLS, DOLS and canonical cointegration regression (CCR) methods.

The results of the ARDL bounds test provide evidence for the long- and short-run relationships among study variables. It evidenced that transport infrastructure performance reduces transport energy consumption by using FMOLS, DOLS and CCR methods. Furthermore, the inference of the positive impact of value added in the manufacturing sector on transport energy consumption validates the higher energy demand of the manufacturing sector from a mobility perspective.

The estimated finding of this study is expected to be contributing to policy-making discussions on transport infrastructure and manufacturing sector development in an emerging economy like India with insights on energy consumption.

To the best of the authors’ knowledge, this is the first study that integrates the impact of manufacturing sector output on transport sector energy consumption along with transport infrastructure performance and public investment in the transport infrastructure.

Tourism development is critical for economic transformation, particularly in emerging economies. However, the growing spate of terrorism dissuades international tourists, reduces tourism receipts and ultimately hampers the tourism sector's performance. Thus, the government intervenes by altering its military spending to curtail terrorism. Against this backdrop, this study examines the moderating role of military spending in the terrorism–tourism nexus in Nigeria.

The study employs the dynamic ordinary least squares (DOLS) to investigate the moderating role of military spending in the terrorism–tourism nexus in Nigeria. The authors employ the data that cover the period 1995Q1–2019Q4.

The results reveal that terrorism has a catastrophic effect on tourism arrivals in Nigeria while military spending has a positive impact on tourism arrivals. The results further show the moderating role of military spending in the terrorism–tourism nexus is positive and statistically significant. However, the findings are subject to the measures of military spending, terrorism and tourism.

The practical implication of the findings is the need for deliberate and strategic budgeting for the Ministry of Defence to combat terrorism, which should not only focus on the procurement of arms and ammunition but also cover the welfare of the military personnel. Nigeria also needs to formulate and implement necessary tourism policies aimed at countering terrorism in a bid to create and maintain a positive image on the global tourist map.

Many studies, particularly in developing countries like Nigeria, had examined the effect of terrorism on tourism but none has examined the moderating role of military spending in the terrorism–tourism nexus. Hence, this study examines the moderating role of military spending in the relationship between terrorism and tourism in Nigeria, a terrorism-prone country with several tourist sites.

Despite the huge financial resources associated with oil, Nigeria has consistently recorded poor growth performance. Therefore, this study aims to examine how corruption and oil rent influence Nigeria’s economic performance during the 1996–2021 period.

Various estimation techniques were used. These include the bootstrap autoregressive distributed lag (ARDL) bounds-testing, dynamic ordinary least squares (DOLS), the fully modified OLS (FMOLS) and the canonical cointegration regression (CCR) estimators and the Toda–Yamamoto causality.

The bounds testing results provide evidence of a cointegrating relationship between the variables. In addition, the results of the ARDL, DOLS, CCR and FMOLS estimators demonstrate that oil rent and corruption have a significant positive impact on growth. Further, the results indicate that human capital and financial development enhance economic growth, whereas domestic investment and unemployment rates slow down long-term growth. Additionally, the causality test results illustrate the presence of a one-way causality from oil rent to economic growth and a bi-directional causal relationship between corruption and economic growth.

Existing studies focused on the effects of either oil rent or corruption on growth in Nigeria. Little attention has been paid to the exploration of how the rent from oil and the pervasiveness of corruption contribute to the performance of the Nigerian economy. Based on the outcome of this study, strategies and policies geared towards reducing oil dependence and the pervasiveness of corruption, enhancing human capital and financial development and reducing unemployment are recommended.

This study aims to assess the nexus among oil price (OP), renewable energy consumption (REC) and trade balance (TB) for India using annual time series data for the time period 1985–2019. In particular, the authors examine whether REC improves India's TB in the context of high oil import dependence.

The study uses autoregressive distributed lags (ARDL) bound testing approach that has the advantage of yielding estimates of long-run and short-run parameters simultaneously. Moreover, the small sample properties of this approach are superior to other multivariate cointegration techniques. Fully modified ordinary least square (FMOLS) and dynamic ordinary least squares (DOLS) are also applied to test the robustness of the results. The causality among the series is investigated through block exogeneity test based on vector error correction model.

The findings based on ARDL bounds testing approach indicate that OPs exert a negative impact on TB of India in both long run and short run, whereas REC has a favorable impact on the TB. In particular, 1% increase in OPs decreases TBs by 0.003% and a 1% increase in REC improves TB by 0.011%. The results of FMOLS and DOLS corroborate the findings from ARDL estimates. The results of block exogeneity test suggest unidirectional causation from OPs to TB; OPs to REC and REC to TB.

The study underscore the importance of renewable energy as a potential tool to curtail trade deficits in the context of Indian economy. Our results suggest that the policymakers must pay attention to the hindrances in augmentation of renewable energy usage and try to capitalize on the resulting gains for the TB.

Climate change is a major challenge for developing countries like India. Renewable energy sector is considered an important instrument toward attaining the twin objectives of environmental sustainability and employment generation. This study underscores another role of REC as a tool to achieve a sustainable trade position, which may help India save her valuable forex reserves for broader objectives of economic development.

To the best of the authors’ knowledge, this is the first study that probes the dynamic nexus among OPs, REC and TB in Indian context. From a policy standpoint, the study underscores the importance of renewable energy as a potential tool to curtail trade deficits in context of India. From a theoretical perspective, the study extends the literature on the determinants of TB by identifying the role of REC in shaping TB.

This paper investigates a problem in a reverse logistics (RLs) network to decide whether to dispose of unsold goods in primary stores or re-commercialize them in outlet centers. By deducting the costs associated with each policy from its revenue, this study aims to maximize the profit from managing unsold goods.

A new mixed-integer linear programming model has been developed to address the problem, which considers the selling prices of products in primary and secondary stores and the costs of transportation, cross-docking and returning unwanted items. As a result of uncertain nature of the cost and time parameters, gray numbers are used to deal with it. In addition, an innovative uncertain solution approach for gray programming problems is presented that considers objective function satisfaction level as an indicator of optimism.

According to the results, higher costs, including transportation, cross-docking and return costs, make sending goods to outlet centers unprofitable and more goods are disposed of in primary stores. Prices in primary and secondary stores heavily influence the number of discarded goods. Higher prices in primary stores result in more disposed of goods, while higher prices in secondary stores result in fewer. As a result of the proposed method, the objective function satisfaction level can be viewed as a measure of optimism.

An integral contribution of this study is developing a new mixed-integer linear programming model for selecting the appropriate goods for re-commercialization and choosing the best outlet center based on the products' price and total profit. Another novelty of the proposed model is considering the matching percentage of boxes with secondary stores’ desired product lists and the probability of returning goods due to non-compliance with delivery dates. Moreover, a new uncertain solution approach is developed to solve mathematical programming problems with gray parameters.

This research paper aims to explore the impact artisan cooperatives have upon women employed in Sub-Saharan Africa. Impacts were detailed using the theoretical framework of social capital theory to demonstrate the networks within artisan cooperatives that connect to greater opportunities for social and economic benefits.

A phenomenological approach was used for this study based upon the shared experiences of women who were leading artisan cooperatives in Sub-Saharan Africa. This study included semi-structured interviews over Zoom with Chief Entrepreneur Founders of artisan cooperatives located in Sub-Saharan Africa. Documents from the cooperatives were analyzed to triangulate the cooperatives’ current projects and efforts.

Three prevalent themes emerged: (1) key partnerships, (2) benefits of the cooperative and (3) change and growth among the women and communities. Empowerment was felt through both economic and social impacts upon the women.

This article captures the perspective of the Chief Entrepreneur Founders and their observations and experiences the women shared with them. Emic perspectives from the women who participate in the artisan cooperatives is the focus of future research.

These social enterprises serve as exemplary models for other cooperatives to provide dignified and sustainable work to impact the lives of women serving in these communities.

This study contributes research on social entrepreneurship within artisan cooperatives. It provides a baseline for further research on the artisan sector specifically for the sustainable development goals of gender equality, decent work and economic growth.