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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.

This study aims to explore the use of a double diamond design method to engage the industry in a sector-wide response to the issues of food waste as constructed by consumers. This particular design method is achieved by an exploration of a collective intelligence-participatory design (CIPD) project to engage industry participants in understanding and responding to consumers’ perceptions of the role of packaging in reducing food waste.

Using the UK Design Council’s double diamond design method as a guiding conceptual principle, the project recruited industry participants from medium to large food businesses across various food categories. Two scoping workshops with industry were held prior to the initiation of a 12-stage project (n = 57), and then two industry workshops were held (n = 4 and 14). Eighty participants completed an online qualitative survey, and 23 industry participants took part in a Think Tank Sprint Series. The Think Tanks used participatory design approaches to understand barriers and opportunities for change within food industry sub-sectors and test the feasibility and acceptability of package designs to reduce consumer waste.

For CIPD to work for complex problems involving industry, it is vital that stakeholders across macro- and micro-subsystems are involved and that adequate time is allowed to address that complexity. Using both the right tools for engagement and the involvement of the right mix of representatives across various sectors of industry is critical to reducing blame shift. The process of divergence and convergence allowed clear insight into the long-term multi-pronged approach needed for the complex problem.

Participatory design has been useful within various behaviour change settings. This paper has demonstrated the application of the double diamond model in a social marketing setting, adding value to an industry-wide project that included government, peak bodies, manufacturing and production and retailers.

Indian railways (IR) is one of the largest railway networks in the world. As a part of its strategic development initiative, demand forecasting can be one of the indispensable activities, as it may provide basic inputs for planning and control of various activities such as coach production, planning new trains, coach augmentation and quota redistribution. The purpose of this study is to suggest an approach to demand forecasting for IR management.

A case study is carried out, wherein several models i.e. automated autoregressive integrated moving average (auto-ARIMA), trigonometric regressors (TBATS), Holt–Winters additive model, Holt–Winters multiplicative model, simple exponential smoothing and simple moving average methods have been tested. As per requirements of IR management, the adopted research methodology is predominantly discursive, and the passenger reservation patterns over a five-year period covering a most representative train service for the past five years have been employed. The relative error matrix and the Akaike information criterion have been used to compare the performance of various models. The Diebold–Mariano test was conducted to examine the accuracy of models.

The coach production strategy has been proposed on the most suitable auto-ARIMA model. Around 6,000 railway coaches per year have been produced in the past 3 years by IR. As per the coach production plan for the year 2023–2024, a tentative 6551 coaches of various types have been planned for production. The insights gained from this paper may facilitate need-based coach manufacturing and optimum utilization of the inventory.

This study contributes to the literature on rail ticket demand forecasting and adds value to the process of rolling stock management. The proposed model can be a comprehensive decision-making tool to plan for new train services and assess the rolling stock production requirement on any railway system. The analysis may help in making demand predictions for the busy season, and the management can make important decisions about the pricing of services.

The MENA region is very rich in terms of natural resources. At the same time, the MENA region has also been a victim of terrorism during the last few years. This study is an attempt to investigate whether there is any relationship between natural resources and terrorism in the MENA region.

We have focused on 15 resource-rich countries located in the MENA region for the period 2002–2019. We have applied appropriate econometric techniques and have also controlled for other dominant determinants of terrorism while studying the relationship between these two variables.

The results provide solid evidence in favor of the hypothesis that natural resources encourage terrorism. We find that natural resources have positively impacted terrorism. Besides, the natural resources, other factors such as per capita GDP, trade openness, political stability, domestic investment and government expenditures have negatively impacted terrorism. Moreover, the findings suggest that FDI and corruption are irrelevant in explaining terrorism while the findings regarding employment level and terrorism are unexpected. The obtained results are robust to alternative estimating methodologies.

The results have serious policy implications for the MENA region. The MENA region in general is suggested to devise appropriate policies regarding their huge natural resources so as to tackle the terrorism problem effectively. Similarly, paying favorable attention to trade liberalization, political stability, government expenditures, investment, rising income of the population in the presence of macroeconomic stability in the form of lower inflation would also help the MENA region to eradicate the problem of terrorism.

The available literature has largely ignored the role of natural resources in explaining the problem of terrorism. Therefore, this study has provided relatively new evidence regarding the determinants of terrorism.

This study assesses the extent to which integrated extension services contribute to the adoption of climate-smart agriculture (CSA) innovations within the cotton value chain in Burkina Faso.

To address the research question, a probit multivariate econometric model with sample selection is utilized. The model is applied to a random sample of farmers (n = 510), and the endogeneity is addressed through a control function approach.

The study highlights the central role of value chains, particularly in the cotton sector, in overcoming resource scarcity through integrated extension services. Findings show that smallholder farmers who benefit from sound extension services are more willing to adopt and diversify CSA technologies. These include improved seeds, conservation techniques, adapted planting dates and mechanization. This study confirms the synergistic nature of these technologies and emphasizes that effective climate risk mitigation depends on the combined adoption of CSA technologies.

The use of cross-sectional data limits the analysis of long-term farmer behavior, and due to data limitations, the focus was primarily on the contributions of cotton companies and farmers to climate risk mitigation. Future research using panel data across the value chain could provide a more robust insights for policy decision-making.

The study contributes to the existing body of knowledge by emphasizing the crucial role of integrated extension services within the cotton value chain in developing countries. This highlights the critical benefits for farmers and emphasizes the need to diversify modern technologies to effectively combat climate change and its variability in agriculture.

The purpose of this study is to examine whether the gender of an audit engagement partner (EP) is associated with the quality of the EP’s audit output.

This paper defines a low-quality EP as an EP who leads the audit of at least one client firm that subsequently restates its financial statements, while a high-quality EP is an EP that is not associated with any restatement. Using a sample of 6,082 observations from 2016 to 2020, the study estimates a logistic regression of EP quality on EP gender and control variables.

The results show that female EPs are more likely to be high-quality EPs. With an odds ratio of 1.25, the results imply that female EPs are 1.25 times more likely to be associated with higher-quality audits compared to male EPs.

The results of this study imply that female EPs are more likely to perform high-quality audits, and it supports the assertion that EP gender plays a significant role in determining EP quality. Further studies may apply gender theory to investigate the behavior of female EPs.

The results show that female EPs are more likely to be high-quality EPs. With an odds ratio of 1.25, the results imply that female EPs are 1.25 times more likely to be associated with higher-quality audits compared to male EPs.

The results of this study should be of interest to stakeholders such as audit committees, regulators, investors and creditors, as they provide an indicator for assessing the quality of audits. Moreover, considering the EP’s important role in an audit, the current study extends the existing literature by providing evidence of a relationship between EP gender and EP quality.

The research aims to explore the relationships between the digital capabilities of micro, small and medium enterprises (MSMEs), their participation in global value chains and their adoption of innovative business models. Additionally, the study investigates how the prior experiences of entrepreneurial failure may influence or moderate these relationships.

To address these research objectives, the study draws upon data obtained from the Flash Eurobarometer 486 survey, a comprehensive dataset that explores the challenges faced by 13,197 European MSMEs as they navigate the complexities of growth, the integration of sustainable business models and the incorporation of digital technologies. To test the proposed hypotheses, the research employs multivariate logistic regression analysis.

Digital capabilities are found to be positively associated with business model innovation, while integration into global value chains is linked to a higher likelihood of implementing new business models. Interestingly, entrepreneurial failure did not significantly influence the relationship between digital capabilities and the adoption of new business models. In contrast, entrepreneurial failure significantly moderated the impact of global value chain inclusion on business model innovation, particularly in MSMEs with a history of failure.

This article provides practical guidance to entrepreneurs and companies interested in enhancing their digital strategies and engagement in global value chains, considering the entrepreneurs' business histories.

The Sustainable Development Goal (SDG) 16 outlines sustainability as associated with peace, good governance and justice. The perception of international tourists about security measures and risks is a key factor affecting destination choices, tourist flow and overall satisfaction. Thus, we investigate the impact of armed forces personnel, prices, economic stability, financial development and infrastructure on tourism.

This research used data from 130 countries from 1995 to 2019, which were divided into four income groups. This study employs a two-step generalized method of moments (GMM) technique and a novel tourism index comprising five relevant indicators of tourism.

A 1% increase in armed forces personnel expands tourism in all income groups – 0.369% High Income Countries (HICs), 0.348% Upper Middle Income Countries (UMICs), 0.247% Lower Middle Income Countries (LMICs) and 0.139% Low Income Countries (LICs). The size of the tourism-safety coefficient decreases from high to low-income groups. The impact of inflation is significantly negative in all panels, excluding LICs. The reduction in tourism was 0.033% in HICs, 0.049% in UMICs and 0.029% in LMICs for a 1% increase in prices. The increase in the global tourism index is more in LICs (0.055%), followed by LMICs (0.024%), UMICs (0.009%) and HICs (0.004%) for a 1% expansion in the gross domestic product (GDP)/capita growth. However, the magnitude of the growth-led tourism impact is greater in developing countries. A positive impact of foreign direct investment (FDI) inflow was found in all panels like 0.016% in HICs, 0.050% in UMICs and 0.119% in LMICs for a 1% increase in FDI inflow. The rise in the global tourism index is 0.097% (HICs), 0.124% (UMICs) and 0.310% (LMICs) for a 1% rise in the financial development index. The increase in the global tourism index is 0.487% (HICs), 0.420% (UMICs) and 0.136% (LICs) for a 1% rise in the infrastructure index.

Empirical analysis infers important policy implications such as (a) establishment of a peaceful environment via recruitment of security personnel, use of safe city cameras, modern technology and law enforcement; (b) provision of basic facilities to tourists like sanitation, drinking water, electricity, accommodation, quality food, fuel and communication network and (c) price stability through different tools of monetary and fiscal policy.

First, it explains the effect of security personnel on a comprehensive index of tourism instead of a single variable of tourism. Second, it captures the importance of economic stability (i.e., economic growth, financial development and FDI inflow) in the tourism–peace nexus.

This study aims to study the thermal identification issue by harvesting both solar energy and atmospheric thermal updraft for a solar-powered unmanned aerial vehicle (SUAV) and its electric energy performance under continuous soaring conditions.

The authors develop a specific dynamic model for SUAVs in both soaring and cruise modes. The support vector machine regression (SVMR) is adopted to estimate the thermal position, and it is combined with feedback control to implement the SUAV soaring in the updraft. Then, the optimal path model is built based on the graph theory considering the existence of several thermals distributed in the environment. The procedure is proposed to estimate the electricity cost of SUAV during flight as well as soaring, and making use of dynamic programming to maximize electric energy.

The simulation results present the integrated control method could allow SUAV to soar with the updraft. In addition, the proposed approach allows the SUAV to fly to the destination using distributed thermals while reducing the electric energy use.

Two simplified dynamic models are constructed for simulation considering there are different flight mode. Besides, the data-driven-based SVMR method is proposed to support SUAV soaring. Furthermore, instead of using length, the energy cost coefficient in optimization problem is set as electric power, which is more suitable for SUAV because its advantage is to transfer the three-dimensional path planning problem into the two-dimensional.

This study aims to address the macroeconomic factors effect on the travel and leisure (T&L) industry throughout Europe within the context of the Russo-Ukrainian war that have started on 24 February 2022. Specifically, top tourist destinations are analysed, such as Spain, France, Italy and Portugal, as well as Europe in general.

This study adopts the panel regression approach based on the data that is provided on a daily basis, and it covers a period of nearly 14 months, starting on 24 February 2022 and ending on 15 April 2023.

The findings indicate that the European T&L sector is impacted by macroeconomic variables. Namely, the T&L sector is significantly impacted by interest rates, geopolitical risk, oil and gas, whereas inflation has a muted effect, indicating a comparatively lesser influence on the dynamics of the industry. This research contributes to existing literature by providing one of the first quantitative analyses of how macroeconomic factors impact the European T&L business in the context of a geopolitical conflict.

A study of the Russian–Ukrainian war may be limited by a number of research constraints. The continuing nature of the conflict, the lack of communication between the parties and potential political prejudice are some of these difficulties. Any research on the Russo-Ukrainian war should be done with these limits in mind.

Macroeconomic variables play a significant role on the T&L sector development; therefore, when designing resilience strategies, they need to be accounted for.

To the best of authors’ knowledge, this is one of the first studies to analyse how macroeconomic factors affected the European T&L business using a quantitative approach. The macroeconomic variables that were taken into account in this study included interest rates, inflation, oil and petrol prices, as well as the geopolitical risk index.