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Most empirical papers on threshold effects between debt and growth focus on developed countries or a mix of developing and developed economies, often using public debt. Evidence for developing economies is inconclusive, as is the analysis of other threshold effects such as those probably caused by the level of relative development or the repayment capacity. The objective of this study was to examine threshold effects for developing economies, including external and total debt, and identify them in the debt-growth relation considering three determinants: debt itself, initial real Gross Domestic Product (GDP) per capita and debt to exports ratio.

We used a panel threshold regression model (PTRM) and a dynamic panel threshold model (DPTM) for a sample of 47 developing countries from 1970 to 2019.

We found (1) no evidence of threshold effects applying total debt as a threshold variable; (2) one critical value for external debt of 42.32% (using PTRM) and 67.11% (using DPTM), above which this factor is detrimental to growth; (3) two turning points for initial GDP as a threshold variable, where total and external debt positively affects growth at a very low initial GDP, it becomes nonsignificant between critical values, and it negatively influences growth above the second threshold; (4) one critical value for external debt to exports using PTRM and DPTM, below which external debt positively affects growth and negatively above it.

The outcome suggests that only poorer economies can leverage credits. The level of the threshold for the debt to exports ratio is higher than that found in previous literature, implying that the external restriction could be less relevant in recent periods. However, the threshold for the external debt-to-GDP ratio is lower compared to previous evidence.

This study provides the critical masses (thresholds) at which the positive incidence of finance and economic growth will be dampened by the negative effects of income inequality and poverty on energy consumption in Sub-Saharan Africa for policy direction.

The study employed the two steps systems GMM estimator for 41 countries in Africa from 2005–2020.

The study found that for finance to maintain a positive effect on energy consumption per capita, the critical thresholds for the income inequality indicators (Atkinson coefficient, Gini index and the Palma ratio) should not exceed 0.681, 0.582 and 5.991, respectively. Similarly, for economic growth (GDP per capita growth) to maintain a positive effect on energy consumption per capita, the critical thresholds for the income inequality indicators (Atkinson coefficient, Gini index and the Palma ratio) should not exceed 0.669, 0.568 and 6.110, respectively. On the poverty level in Sub-Saharan Africa, the study reports that the poverty headcount ratios (hc$144ppp2011, hc$186ppp2011 and hc$250ppp2005) should not exceed 7.342, 28.278 and 129.332, respectively for financial development to maintain a positive effect on energy consumption per capita. The study also confirms the positive nexus between access to finance (financial development) and energy consumption per capita, with the attending adverse effect on CO₂ emissions inescapable. The findings of this study make it evidently clear, for policy recommendation that finance is at the micro-foundation of economic growth, income inequality and poverty alleviation. However, a maximum threshold of income inequality and poverty headcount ratios as indicated in this study must be maintained to attain the full positive ramifications of financial development and economic growth on energy consumption in Sub-Saharan Africa.

The originality of this study is found in the computation of the threshold and net effects of poverty and income inequality in economic growth through the conditional and unconditional effects of finance.

“The unexamined life is not worth living” (Socrates). That is, without critically inquiring into the knowledge of life which is well-being and valuable, life is not worth living. Critical thinking questions existing theories and their unexamined and obsessive assumptions and generalizations, constraints, and “best” practices of the prevailing system of management and tries to replace them with more valid assumptions and generalizations that uphold the dignity, uniqueness, and inalienable rights of the individual person and the community. Better outcomes result from asking the right questions than from having the right answers. In the diverse, pluralist cultural environment of today, the promise of a truly generative dialog among Occidental (Western) and Oriental (Eastern) cultures and civilizations holds great hope for the future. Critical thinking (CT) is an “inclusive” thinking system that can facilitate this dialog such that all of us have a meaningful space and place in this universe. After defining CT and arguing its importance for executives, this chapter introduces CT in two parts: Part 1: Various Approaches to Critical Thinking; Part 2: Major Theories of Critical Thinking. Several contemporary business cases will be invoked to illustrate the need, nature, and scope of corporate CT.

The purpose of this paper is to search for the critical-scenarios of autonomous vehicles (AVs) quickly and comprehensively, which is essential for verification and validation (V&V).

The author adopted the index F1 to quantitative critical-scenarios' coverage of the search space and proposed the improved particle swarm optimization (IPSO) to enhance exploration ability for higher coverage. Compared with the particle swarm optimization (PSO), there were three improvements. In the initial phase, the Latin hypercube sampling method was introduced for a uniform distribution of particles. In the iteration phase, the neighborhood operator was adapted to explore more modals with the particles divided into groups. In the convergence phase, the convergence judgment and restart strategy were used to explore the search space by avoiding local convergence. Compared with the Monte Carlo method (MC) and PSO, experiments on the artificial function and critical-scenarios search were carried out to verify the efficiency and the application effect of the method.

Results show that IPSO can search for multimodal critical-scenarios comprehensively, with a stricter threshold and fewer samples in the experiment on critical-scenario search, the coverage of IPSO is 14% higher than PSO and 40% higher than MC.

The critical-scenarios' coverage of the search space is firstly quantified by the index F1, and the proposed method has higher search efficiency and coverage for the critical-scenarios search of AVs, which shows application potential for V&V.

This study examines the relevance of information and communication technologies in the effect of gender economic inclusion on environmental sustainability.

The focus is on a panel of 42 sub-Saharan African countries over the period 2005–2020. The empirical evidence is based on generalized method of moments. The environmental sustainability indicator used is CO2 emissions per capita. Three indicators of women’s economic inclusion are considered: female labour force participation, female employment and female unemployment. The chosen ICT indicators are mobile phone penetration, Internet penetration and fixed broadband subscriptions.

The results show that: (1) fixed broadband subscriptions represent the most relevant ICT moderator of gender economic inclusion for an effect on CO2 emissions; (2) negative net effects are apparent for the most part with fixed broadband subscriptions (3) both positive ICT thresholds (i.e., critical levels for complementary policies) and negative ICT thresholds (i.e., minimum ICT levels for negative net effects) are provided; (4) ICT synergy effects are apparent for female unemployment, but not for female employment. In general, the joint effect of ICTs or their synergies and economic inclusion should be a concern for policymakers in order to better ensure sustainable development. Moreover, the relevant ICT policy thresholds and mobile phone threshold for complementary policy are essential in promoting a green economy.

The study complements the extant literature by assessing linkages between information technology, gender economic inclusion and environmental sustainability.

This paper aims to shed light on an impact of Google keywords on the number of new businesses (and an amount of capital registered) in Vietnam, the Southeast Asian country, after the year of an entrepreneur, 2016.

This study uses a rich set of quantitative techniques from VAR Granger and threshold regression. The whole sample period covers the data (keywords, number of new businesses, an amount of capital invested to register) from the first week of 2016 to October 2018, which includes 144 observations in total.

The findings suggest that the relationship between Google does not persist in the long run. There is a short-run shock, might cause a change to the frequency of the other keywords rather than the number of firms (or an amount of capital). However, under the number of firms’ threshold, keywords have the both positive and negative impacts on entrepreneurs whereas a higher threshold of capital, keywords show their roles to predict an amount of money for registering firms.

The Vietnamese Government and executives are advised to consider the Google keywords “entrepreneur” (in Vietnamese) and “start-up”, which cause a decline in entrepreneurial movements. In addition, the current period is going to inverse from the previous one in terms of the number of firms and an amount of capital. Finally, there are two critical thresholds: 1,602 companies and 35,010m VND for the keywords' influence.

This study contributes empirical evidence of technological change and entrepreneurship and contributes to the existing literature by discussing how this relationship under the threshold.

The anticipated benefits of connected and autonomous vehicles (CAVs) include safety and mobility enhancement. Small headways between successive vehicles, on one hand, can cause increased capacity and throughput and thereby improve overall mobility. On the other hand, small headways can cause vehicle occupant discomfort and unsafety. Therefore, in a CAV environment, it is important to determine appropriate headways that offer a good balance between mobility and user safety/comfort.

In addressing this research question, this study carried out a pilot experiment using a driving simulator equipped with a Level-3 automated driving system, to measure the threshold headways. The Method of Constant Stimuli (MCS) procedure was modified to enable the estimation of two comfort thresholds. The participants (drivers) were placed in three categories (“Cautious,” “Neutral” and “Confident”) and 250 driving tests were carried out for each category. Probit analysis was then used to estimate the threshold headways that differentiate drivers' discomfort and their intention to re-engage the driving tasks.

The results indicate that “Cautious” drivers tend to be more sensitive to the decrease in headways, and therefore exhibit greater propensity to deactivate the automated driving mode under a longer headway relative to other driver groups. Also, there seems to exist no driver discomfort when the CAV maintains headway up to 5%–9% shorter than the headways they typically adopt. Further reduction in headways tends to cause discomfort to drivers and trigger take over control maneuver.

In future studies, the number of observations could be increased further.

The study findings can help guide specification of user-friendly headways specified in the algorithms used for CAV control, by vehicle manufacturers and technology companies. By measuring and learning from a human driver's perception, AV manufacturers can produce personalized AVs to suit the user's preferences regarding headway. Also, the identified headway thresholds could be applied by practitioners and researchers to update highway lane capacities and passenger-car-equivalents in the autonomous mobility era.

The study represents a pioneering effort and preliminary pilot driving simulator experiment to assess the tradeoffs between comfortable headways versus mobility-enhancing headways in an automated driving environment.

This study aims to examine the relationship between female directors and bank risk. In particular, whether such a relationship varies across sound or unsound banks and with or without a critical mass of female directors is tested.

Using a sample of 215 listed banks from 40 countries over the period 2008–2016, this study carries out panel data analyses and tests all the model specifications on four different measures of risk (common equity ratio, leverage, NPLs ratio and price volatility).

The findings show that increasing the number of female directors does not reduce bank risk when banks are unsound. When banks are sound, female directors have a significant and positive role in reducing risk, only until reaching a critical mass of women.

This study provides useful corporate governance indications for policymakers and practitioners. Advantages of gender diversity on boards are recognized especially in sound banks, but increasing the number of women directors beyond the critical mass may not lead to lower risk. In fact, ethical or legal pressures aimed at increasing gender diversity on boards (i.e. soft or hard gender quotas) may cause undesired effects on bank risk, especially if female directors are not chosen on merit and skills. Moreover, gender-balanced boards, namely, with a “dual critical mass,” seem to assure more effective decision-making processes.

This study provides empirical evidence on female board members and risk minimization, differentiating between sound or unsound banks. Furthermore, this study contributes to the literature on the critical mass of women on the board of directors by testing this theory for these two categories of banks.

The purpose of this paper is to generalize the traditional risk evaluation methods and to specify a multi-level risk evaluation framework, in order to prepare customized risk evaluation and to enable effectively integrating the elements of risk evaluation.

A real case study of an electric motor manufacturing company is presented to illustrate the advantages of this new framework compared to the traditional and fuzzy failure mode and effect analysis (FMEA) approaches.

The essence of the proposed total risk evaluation framework (TREF) is its flexible approach that enables the effective integration of firms’ individual requirements by developing tailor-made organizational risk evaluation.

Increasing product/service complexity has led to increasingly complex yet unique organizational operations; as a result, their risk evaluation is a very challenging task. Distinct structures, characteristics and processes within and between organizations require a flexible yet robust approach of evaluating risks efficiently. Most recent risk evaluation approaches are considered to be inadequate due to the lack of flexibility and an inappropriate structure for addressing the unique organizational demands and contextual factors. To address this challenge effectively, taking a crucial step toward customization of risk evaluation.