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This research investigates the threshold effects of the interplay between finance, development and carbon emissions across 97 countries, including 50 low-income and 47 high-income countries, during the period from 1991 to 2019.

Employing various econometric modeling techniques such as dynamic linear regression, dynamic panel threshold regression and in/out of sample splitting, this study analyzes the data obtained from the World Bank's world development indicators.

The results indicate that low-income countries require a minimum financial development threshold of 0.354 to effectively reduce carbon emissions. Conversely, high-income countries require a higher financial development threshold of 0.662 to mitigate finance-induced carbon emissions. These findings validate the presence of a finance-led Environmental Kuznet Curve (EKC). Furthermore, the study highlights those high-income countries exhibit greater environmental concern compared to their low-income counterparts. Additionally, a minimum GDP per capita of US$ 10,067 is necessary to facilitate economic development and subsequently reduce carbon emissions. Once GDP per capita surpasses this threshold, a rise in economic development by a certain percentage could lead to a 0.96% reduction in carbon emissions across all income levels.

This study provides a novel contribution by estimating practical financial and economic thresholds essential for reducing carbon emissions within countries at varying levels of development.

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.

The purpose of this study is to investigate if a firm's exchange complexity profile (that is, the linkages between the firm and its environment) influences investor behavior at the negotiation table where a firm valuation is derived.

The authors utilize Qualitative Comparative Analysis (QCA). Specifically, the authors utilize fuzzy-set Qualitative Comparative Analysis (fsQCA), a QCA variant that allows the researcher to assign graduated membership in sets.

When the authors dichotomize their positions as either higher stakes that favor the seller (high capital, low equity, high valuation) or lower stakes that favor the buyer (low capital, high equity, low valuation), and when the authors focus primarily on the equity outcome, the authors find that investors adopt a reductionist stance that adheres to a transaction cost economics logic under conditions of lower stakes and higher complexity as well as higher stakes and lower complexity conditions. The authors interpret this to mean that equity serves as a counter-balancing lever for a firm's exchange complexity configuration.

On a theoretical level, the authors showcase the exchange complexity framework and differentiate its position within the extant frameworks that address a firm's competitive advantage. More generally, the authors note that this framework brings the discipline of micro-economics and the field of strategic management closer together, providing scholars with a new tool enabling research across industries for the portfolio level of analysis.

Previous research suggests that the compensation offered to customers after a service failure has to be substantial to make customer satisfaction surpass that of an error-free service. However, with the right service recovery strategy, it might be possible to reduce compensation size while maintaining happy customers. The aim of the current study is to test whether an anchoring technique can be used to achieve this goal.

After experiencing a service failure, participants were told that there is a standard size of the compensation for service failures. The size of this standard was different depending on condition. Thereafter, participants were asked how much they would demand to be satisfied with their customer experience.

The compensation demand was relatively high on average (1,000–1,400 SEK, ≈ $120). However, telling the participants that customers typically receive 200 SEK as compensation reduced their demand to about 800 SEK (Experiment 1)—an anchoring effect. Moreover, a precise anchoring point (a typical compensation of 247 SEK) generated a lower demand than rounded anchoring points, even when the rounded anchoring point was lower (200 SEK) than the precise counterpart (Experiment 2)—a precision effect.

Setting a low compensation standard—yet allowing customers to actually receive compensations above the standard—can make customers more satisfied while also saving resources in demand-what-you-want service recovery situations, in particular when the compensation standard is a precise value.

This study intends to explore the relationship between digital finance and the vertical specialization of firms. The following questions are discussed: (1) As a representative new financial development model, what is the role of digital finance in the vertical specialization of firms? (2) If digital finance improves the level of vertical specialization of firms, what is the mechanism behind such improvement? (3) How does digital finance impact the vertical specialization of firms in different regions, industries, and firms?

A two-way fixed-effect model of panel data is proposed to verify the relationship between digital finance and the vertical specialization of firms. This model is constructed by matching the city-level data of digital finance with the data of China's A-share listed companies from 2011 to 2018. Meanwhile, the instrumental variable (IV) method and difference-in-difference (DID) method are adopted to deal with the endogeneity problem of the model.

The authors' study finds that digital finance has significantly improved the level of vertical specialization of firms. The result is robust under the endogeneity consideration and a series of robustness tests. After the dimensionality of the index is reduced, the depth of digital finance usage is more conducive to the improvement of the vertical specialization of firms compared with the width of digital finance coverage and the level of financial digitization. Digital finance mainly improves the level of vertical specialization of firms by reducing transaction costs and increasing the market thickness of the intermediate products. Moreover, digital finance has certain heterogeneity in promoting the vertical specialization of firms, an effect that is more significant in the eastern region, manufacturing industry and state-owned enterprises (SOEs).

The first limitation is the mechanism test. This research only analyzes the mechanism from transaction cost and the market thickness of the intermediate products. With the rapid development of information technology, digital finance will be further integrated into people's production and life. There will then be more mechanisms that should be explored between digital finance and the vertical specialization of firms. Another limitation is the data sample of this paper. The conclusions of this research are based only on the data of listed companies. However, in the authors' opinion, the specialization level of small and medium-sized enterprise (SMEs) should be higher. Therefore, the conclusions of this work are underestimated, which can be considered as the lower limit of digital finance for enterprise specialization.

As a favorable financing channel to supplement traditional financial service functions, digital finance plays a critical role in the operating efficiency of enterprises and the effective allocation of macro resources. The authors' research shows that digital finance has significantly improved the vertical specialization of firms. This conclusion provides guides to improve the production efficiency of enterprises and the quality of economic development.

This paper has three main contributions. (1) The relationship between financial development and the vertical specialization of firms is innovatively discussed from the perspective of digital finance, which implies that digital finance can effectively promote the level of vertical specialization of firms. (2) This paper provides new perspectives and ideas to reveal the impact mechanism of digital finance on the real economy by systematically analyzing the mechanism of digital finance on the vertical specialization of firms from the perspectives of transaction costs and financing constraints. (3) The regional differences in the development of digital finance, industry differences in the vertical specialization of firms and differences in the nature of enterprise property rights are all under consideration, which improves the effectiveness and pertinence of digital finance in promoting the vertical specialization of firms.

This study aims to investigate the most effective approach for governments and enterprises to combat desertification by considering the governance cycle. The focus is on understanding how the government can incentivize enterprises to actively engage in desertification combat efforts.

Both the government and the enterprise are treated as rational entities, making strategic choices for joint participation in combating desertification. Recognizing the dynamic nature of the desertification combat area, differential game models are employed to identify the optimal mode for combating desertification.

The findings underscore the significant influence of the governance cycle duration on the selection of desertification combat modes for government and enterprise. A cooperative mode is best suited to a short governance cycle, while an ecological subsidy mode is optimal for a longer cycle. Enhancing governance technology and shortening the governance cycle are conducive to combating desertification. Reducing taxes alone may not be an effective control strategy; rather, the government can better motivate enterprises by adopting tax rate policies aligned with the chosen governance mode.

This research contributes by elucidating the impact mechanism of the government cycle’s length on the desertification combat process. The results may offer valuable insights for governments in formulating strategies to encourage corporate participation in combating desertification and provide theoretical support for selecting optimal desertification combat modes.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The study focuses on drug safety regulation capture, reveals the inner mechanism and evolutionary characteristics of drug safety regulation capture and provides suggestions for effective regulation by pharmacovigilance.

The article introduces prospect theory into the game strategy analysis of drug safety events, constructs a benefit perception matrix based on psychological perception and analyzes the risk selection strategies and constraints on stable outcomes for both drug companies and drug regulatory authorities. Moreover, simulation was used to analyze the choice of results of different parameters on the game strategy.

The results found that the system does not have a stable equilibrium strategy under the role of cognitive psychology. The risk transfer coefficient, penalty cost, risk loss, regulatory benefit, regulatory success probability and risk discount coefficient directly acted in the direction of system evolution toward the system stable strategy. There is a critical effect on the behavioral strategies of drug manufacturers and drug supervisors, which exceeds a certain intensity before the behavioral strategies in repeated games tend to stabilize.

In this article, the authors constructed the perceived benefit matrix through the prospect value function to analyze the behavioral evolution game strategies of drug companies and FDA in the regulatory process, and to evaluate the evolution law of each factor.

Expanding on the real-world financial market framework and considering the current market turmoil, with cryptocurrencies (where contracts for difference (CFDs) are extremely common) (Hasso et al., 2019) displaying unprecedented volatility, the authors aim to test in an online laboratory setting whether displaying a risk warning message is truly effective in reducing the level of risk taken and whether the placement of this method makes a difference.

To explore the impact of risk disclosure framing on risk-taking behavior, the authors conducted an online pair-wise lottery choice experiment. In addition to manipulating risk awareness through the presence or absence of risk warning messages of varying intensity, the authors also considered dynamic inconsistency, cognitive ability and questionnaire-based financial risk tolerance (FRT) scores. The authors aimed to identify potential relationships between these variables and experimentally elicited risk aversion. The authors' study offers valuable insights into the complex nature of risky decision-making and sheds light on the importance of considering dynamic inconsistency in addition to risk awareness and aversion.

The authors' results provide statistical evidence for the efficacy of informative and very salient messages in mitigating risky decision, hinting at several policy implications. The authors also provide some statistical evidence in support of the relationship between cognitive abilities and risk preferences. The authors detect that individual with low cognitive abilities scores display great risk aversion.

This study investigates the impact of risk warning messages on investment decisions in an online laboratory setting – a unique approach. However, the authors go beyond this and also examine the potential influence of dynamic inconsistency on decision-making, adding further value to the literature on this topic. To ensure a comprehensive understanding of the participants, the authors collect data on cognitive ability and FRT using questionnaires. This study provides a simple and cost-effective framework that can be easily replicated in future research – a valuable contribution to the field.

Drawing on the job demands-resources (JD-R) model, this study aims to examine which job demands individuals with diagnosed mental illness perceive to be most challenging as they navigate the workplace, why this is the case and which resources individuals tend to mobilize to meet these demands.

The authors draw on 257 qualitative surveys filled out by individuals with mental illness in various parts of the world.

The findings show that job demands that are common in today's workplace such as a high workload and a stressful environment are considered challenging by individuals with mental illness. Further, the authors show that this is the result of the ideal worker norm consisting of the need to be a steady performer that is confident, resilient and social with which the performer cannot comply on the one hand and the particularities of this population, such as performers' self-perceived low self-esteem, sensitivity to stress, fluctuating symptoms and difficulties with the social aspects of organizational life on the other hand.

The study points to the unique challenges of individuals with mental illness in the workplace and highlights the role human resource management (HRM) can play in providing support to allow this population to meet the demands of one's job more easily and thrive at work.