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This paper aims to study the impact of tax avoidance on corporate risk. It also examines the moderating impact of tax risk on the relationship between tax avoidance and firm risk.

Based on available information in the DATASTREAM database about a sample of French firms listed in the CAC 40 from 2010 to 2022, the study uses the feasible generalized least squares method to investigate the impact of tax avoidance on firm risk and the moderating impact of tax risk. To check the robustness of our results, the authors changed the measurement of variables to identify potential biases and they significantly mitigated the endogeneity concerns using instrumental variable regression. Additional estimations were performed, first by using book-tax differences (BTD) and its components, i.e. temporary and permanent, and second by retesting hypotheses of years before the outbreak of the corona virus disease 2019 (COVID-19) pandemic.

The results show that tax avoidance negatively affects the firm risk while tax risk has a positive effect on firm risk. More importantly, tax risk moderates the negative impact of tax avoidance on the firm risk. When tax avoidance is associated with a high level of tax risk, it leads to a high firm risk. Accordingly, tax avoidance should be considered in conjunction with tax risk when studying the effect put on the firm risk. Further analyses indicate that tax risk moderates the negative relationship between permanent BTD and firm risk.

The major limitation of this study is that it focuses only on French-listed firms, which make it difficult to generalize the results. Furthermore, the authors did not introduce governance variables into our models. An effective governance system and transparent information can reduce some of the perverse effects of risky tax avoidance by reducing the tax avoidance costs. The obtained results are of great interest to researchers who need to include the tax risk concept in their examination of the tax avoidance impacts.

The results are useful for investors wishing to make sound decisions regarding risky tax avoidance practices. Furthermore, the results may signal the need for French policymakers to make more efforts to reduce risky tax avoidance activities that are harmful to investors. They must enforce the existence and the reporting of a tax risk management strategy by firms.

This study contributes to the growing body of literature on the tax avoidance effects with a special focus on firm risk. This study provides the first French evidence of the role of tax risk in the relationship between tax avoidance and firm risk.

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 paper aims to identify the effect of environmental management systems (EMSs), commitment to stakeholders and gender diversity on corporate environmental performance (CEP) and the extent to which an economic crisis moderates these relationships.

A regression analysis was conducted on a sample of 14,217 observations from 1,933 firms from 26 countries from 2002 to 2010. The estimator used is ordinary least squares with heteroscedastic panel-corrected standard errors (PCSEs), which allows us to obtain consistent results in the presence of heteroscedasticity and autocorrelation.

The results show that EMSs and stakeholder engagement are mechanisms that drive CEP but lose their effectiveness in times of crisis. However, the presence of women on boards has a positive effect on CEP that is not affected by an economic crisis.

The study has some limitations that could be addressed in the future. We present board gender diversity as a governance mechanism because its role is strongly related to non-financial performance. Future studies could focus on other corporate governance mechanisms, such as the presence of institutional or long-term investors. In addition, other mechanisms could be found that can counteract poor environmental performance in times of crisis. Finally, it might be useful to contrast these results with the crisis generated by the coronavirus pandemic.

The results obtained have important practical implications at the corporate and institutional levels. At the corporate level, they highlight, as essential contributions, that environmental management systems and stakeholder orientation are not effective in times of economic crisis, except for with the presence of women on the board.

Following the crisis, the European Commission has promoted gender diversity on boards as a mechanism to improve the governance of entities – improving, among other aspects, sustainability. In this sense, another one of the practical implications of the study is support for the policies that the European Union has implemented over the last two decades.

The paper analyses how a crisis affects the moral and cultural institutional mechanisms that promote CEP. Gender diversity on the board of directors not only promotes environmental performance but also appears to be a governance mechanism that ensures this performance in times of crisis when the other mechanisms lose their effectiveness. The study proposes specific policies that help maintain environmental performance in an economic crisis.

This study explores whether and how four main factors of short-branded video content (content matching, information relevance, storytelling and emotionality) facilitate consumer engagement (likes, comments and shares), as well as the moderating effect of the release time (morning, afternoon and evening) in such relationships.

This study uses Python to write programs to crawl relevant data information, such as consumer engagement and short video release time. It combines coding methods to empirically analyze the impact of short-branded video content characteristics on consumer engagement. A total of 10,240 Weibo short videos (total duration: 238.645 h) from 122 well-known brands are utilized as research objects.

Empirical results show that the content characteristics of short videos significantly affected consumer engagement. Furthermore, the release time of videos significantly moderated the relationship between the emotionality of short videos and consumer engagement. Content released in the morning enhanced the positive impact of warmth, excitement and joy on consumer engagement, compared to that released in the afternoon.

The findings provide new insights for the dissemination of products and brand culture through short videos. The authors suggest that enterprises that use brand videos consider content matching, information relevance, storytelling and emotionality in their design.

From a broader perspective, this study constructs a new method for comprehensively evaluating short-branded video content, based on four dimensions (content matching, information relevance, storytelling and emotionality) and explores the value of these dimensions for creating social media marketing success, such as via consumer engagement.

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.

Quality function deployment (QFD) has been widely applied in new product development, but existing research on QFD has some limitations. Primarily, QFD lacks the capability to provide feedback on the satisfaction degree of customer requirements (CRs) according to the actual values of engineering characteristics (ECs). In addition, QFD does not quantitatively consider the interrelationships among ECs. Reverse QFD (R-QFD) was introduced to implement the feedback process. On this basis, this paper quantitatively considers the interrelationships among ECs in the R-QFD model and extends these relationships to encompass combinations of multiple ECs, aiming to improve the inference accuracy of the model.

A nonlinear regression model was established between CRs and ECs, aiming to infer the satisfaction degree of CRs based on the implementation status of ECs. This model considers the interdependencies among ECs and extends the consideration of pairwise EC correlations from every two to every fifteen. Lingo Software is utilized to seek solutions for this program. To facilitate the implementation of the program, a directive to simplify the solution has been proposed.

The experimental results indicate that the interrelationships among ECs significantly affect the inference accuracy of the R-QFD model, thereby verifying the necessity of considering higher-order interrelationships among ECs within the R-QFD framework. Based on the results from data experiments, this paper also proposes research recommendations pertaining to ECs hierarchy for varying quantities of ECs.

The outcomes of this study have further refined the R-QFD model, addressing its limitations of ignoring the interrelationships among ECs. This transformation elevates the R-QFD model from a relatively simple linear model to a nonlinear model formed through modeling, thereby enhancing its accuracy and applicability. In practical terms, this study provides case support for the application of the R-QFD model in manufacturing industry.

Purpose: The prominence of quality education for building sustainable development is undeniable and is distinctly pointed out in 1 of the 14 sustainable development goals (SDGs). In the same context, this study intends to investigate the role of university commitment, perceived organisational prestige, student satisfaction, and perceived employability in enhancing sustainability in higher education.

Need of the Study: To evaluate how student satisfaction mediates the relationship between university commitment, perceived organisational prestige, and perceived employability with sustainable university institutes.

Methodology: An adapted questionnaire was used in this study to capture the perception of 458 management graduates selected through the purposive sampling method. Partial least squares structural equation modelling (PLS-SEM) technique was used to analyse the data with the help of Smart PLS software.

Findings: The results of this study show that student satisfaction is the strongest predictor of sustainable university institutes. University commitment was found to lead to student satisfaction significantly. Furthermore, student satisfaction wasn’t found to play the role of mediator in the proposed model.

Practical Implications: This study aims to fulfil theoretical, research, and management implications for students, higher education institutes (HEIs), and policymakers. HEIs are recommended to instil university commitment, perceived organisational prestige and student satisfaction via various practices and amendments in their curriculum. Students are recommended to enhance their perceived employability to achieve career sustainability.

As the demand for human–robot collaboration in manufacturing applications grows, the necessity for collision detection functions in robots becomes increasingly paramount for safety. Hence, this paper aims to improve the existing method to achieve efficient, accurate and sensitive robot collision detection.

The external torque is estimated by momentum observers based on the robot dynamics model. Because the state of the joints is more accessible to distinguish under the action of the suppression operator proposed in this paper, the mutated external torque caused by joint reversal can be accurately attenuated. Finally, time series analysis (TSA) methods can continuously generate dynamic thresholds based on external torques.

Compared with the collision detection method based only on TSA, the invalid time of the proposed method is less during joint reversal. Although the soft-collision detection accuracy of this method is lower than that of the symmetric threshold method, it is superior in terms of detection delay and has a higher hard-collision detection accuracy.

Owing to the mutated external torque caused by joint reversal, which seriously affects the stability of time series models, the collision detection method based only on TSA cannot detect continuously. The consequences are disastrous if the robot collides with people or the environment during joint reversal. After multiple experimental verifications, the proposed method still exhibits detection capabilities during joint reversal and can implement real-time collision detection. Therefore, it is suitable for various engineering applications.

The aims of the current study were twofold: first, to rank the world’s emerging economies based on a novel National Intellectual Capital Index (NICI) and its components; and second, to examine the impact of NICI and its components on economic growth, measured in terms of real GDP per capita.

We employed principal component analysis (PCA) to construct the novel NICI based on five key socio-economic indicators including (1) national human capital, (2) national structural capital, (3) national relational capital, (4) national informational capital and (5) national innovational capital. These indicators are publicly available for many countries. The index was generated by considering the most appropriate socio-economic indicators as precise measures of NIC from the Penn world table (version 10.0), the World Bank’s database of world governance and development indicators and the KOF globalization across the selected emerging economies.

The empirical findings revealed that national human capital is a significant driver of NIC, corresponding to higher economic growth. This is followed by national informational capital, national relational capital, national innovation capital and national structural capital. Furthermore, results indicate that the contribution of national structural capital is marginal compared to other critical strands of NIC.

NIC is generally considered the most valuable strategic resource for driving knowledge economies, especially in the Industry 5.0 revolution. Ranking emerging economies based on the NICI sheds light on the accumulated stock of NIC and how it contributes to and improves the economic growth of these economies. The stock of NIC is considered a critical success factor for measuring both current and future economic prosperity. Therefore, using the socio-economic indicators of KOFGI as accurate measures of NICI will assist policymakers in formulating and implementing relevant policies to enhance the accumulation of knowledge-based capital, which are critical components of NIC.

To the best of the authors' knowledge, this is the first study of its kind, both theoretically and empirically, to measure the National Intellectual Capital Index (NICI) using the most nascent socio-economic indicators of NIC. Moving forward, this study evaluates the impact of NICI and its components on economic growth, which is a relatively sparse area of research in the context of emerging knowledge economies.

This paper aims to analyse the influence of workforce diversity on the firm’s likelihood to develop organisational innovations. Operationalising human resources diversity is not straightforward, and its effect has been rather overlooked in the context of non-technological innovations. This study analyses the impact of task-related diversity among research and development (R&D) unit workers and women R&D workers, in particular.

To estimate the impact of task-related diversity on firm propensity to undertake organisational innovation, this study uses a generalised linear model (GLM) – with a binomial family and log–log extension. GLMs are used to control problems of over-dispersion, which, in models with binary response variables, could generate inaccurate standard error estimates and provide inconsistent results.

This paper provides three important results. Firstly, employee diversity increases the firm’s propensity to engage in organisational innovations. Secondly, the influence of each facet of task-related diversity varies depending on the type of organisational innovation considered. Thirdly, gender has an effect on the innovation process; this study shows that women play a different role in the production of non-technological innovations.

This paper makes several contributions to the literature. Firstly, it makes a theoretical contribution to research on innovation management by considering the influence of human resources diversity on the development of non-technological innovations. Secondly, this study analyses the role of workforce diversity in an R&D department context to clarify the contribution made by women R&D workers.