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The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

Gamification design is considered an effective way of changing users' health behavior and improving their health management performance. Even though numerous studies have investigated the positive effect of gamification competition on users, little research has considered gamification's ineffectiveness and negative effects. In particular, how gamification competition affects users' technological exhaustion remains unclear.

According to flow theory and related research on gamification, this study discusses the nonlinear relationship between gamification competition and users' technological exhaustion. Furthermore, the authors analyze the moderating effect of user type (socializers and achievers) and users' health condition on this nonlinear relationship. Based on flow theory, the authors propose a series of research hypotheses. To test all research hypotheses, the authors collected information from 407 users via a questionnaire as the data for this study.

The empirical results found a U-shaped relationship between gamification competition and technological exhaustion. Technological exhaustion gradually decreases as competition increases until reaching the lowest point; after that, technological exhaustion gradually increases as competition increases. Further, being a socializer and health condition play a moderating role in the U-shaped relationship between competition and technological exhaustion.

This study's findings not only enrich the related research in flow theory and gamification, but also contribute to the effective design of gamification in health management platforms.

Might the impact of the financial stress on exchange markets be asymmetric and exposed to regime changes? Departing from the existing literature, highlighting that the domestic and foreign financial stress in terms of money market have substantial effects on exchange market, this paper aims to investigate the impacts of the bond yield spreads of three emerging countries (Mexico, Russia, and South Korea) on their exchange market pressure indices using monthly observations for the period 2010:01–2019:12. Additionally, the paper analyses the impact of bond yield spread of the US on the exchange market pressure indices of the three mentioned emerging countries. The authors hypothesized whether the negative and positive changes in the bond yield spreads have varying effects on exchange market pressure indices.

To address the research question, we measure the bond yield spread of the selected countries by using the interest rate spread between 10-year and 3-month treasury bills. At the same time, the exchange market pressure index is proxied by the index introduced by Desai et al. (2017). We base the empirical analysis on nonlinear vector autoregression (VAR) models and an asymmetric quantile-based approach.

The results of the impulse response functions indicate that increases/decreases in the bond yield spreads of Mexico, Russia and South Korea raise/lower their exchange market pressure, and the effects of shocks in the bond yield spreads of the US also lead to depreciation/appreciation pressures in the local currencies of the emerging countries. The quantile connectedness analysis, which allows for the role of regimes, reveals that the weights of the domestic and foreign bond yield spread in explaining variations of exchange market pressure indices are higher when exchange market pressure indices are not in a normal regime, indicating the role of extreme development conditions in the exchange market. The quantile regression model underlines that an increase in the domestic bond yield spread leads to a rise in its exchange market pressure index during all exchange market pressure periods in Mexico, and the relevant effects are valid during periods of high exchange market pressure in Russia. Our results also show that Russia differs from Mexico and South Korea in terms of the factors influencing the demand for domestic currency, and we have demonstrated the role of domestic macroeconomic and financial conditions in surpassing the effects of US financial stress. More specifically, the impacts of the domestic and foreign financial stress vary across regimes and are asymmetric.

This study enriches the literature on factors affecting the exchange market pressure of emerging countries. The results have significant economic implications for policymakers, indicating that the exchange market pressure index may trigger a financial crisis and economic recession.

This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.

The authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.

The study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.

Despite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.

This study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.

This paper aims to prepare third-order nonlinear optical (NLO) organic materials with large nonlinear optimization value, high damage threshold and ultrafast response time.

A series of novel symmetric and asymmetric compounds possessing third-order NLO properties were synthesized using 1,3,5-tribromobenzene as the basis. The photophysical and electrochemical properties, as well as the click reactions, were characterized by means of UV–VIS–NIR absorption spectroscopy and cyclic voltammetry.

The donor–acceptor chromophores were inserted into compound, making the molecule to have a broader absorption in the near-infrared regions and a narrower optical and electrochemical band gap. It also formed an electron-delocalized organic system, which has larger effects on achieving a third-order NLO response. The third-order NLO phenomenon of benzene ring complexes was experimentally studied at 532 nm using Z-scan technology, and some compounds showed the expected NLO properties.

The click products exhibit more NLO phenomena by performing different click combinations to the side groups, opening new perspectives on using the system in a variety of photoelectric applications.

Corporate social responsibility (CSR) and innovation are the two main approaches firms utilize to promote sustainable development. However, as yet, scholars have reached no consensus regarding their precise impact on construction firm performance (CFP), hindering efforts to implement effective sustainable development strategies that improve CFP. In view that a simple linear relationship may not be sufficient to capture their precise pattern, this study aims to unveil the nonlinear impact of CSR and innovation on CFP, especially when construction firms take up a distinct competitive position.

This study first proposed four hypotheses to establish a new theoretical model by incorporating CSR, innovation, CFP and construction firms' competitive position (CFCP). Then the model was tested by using 292 annual observations collected from 75 construction firms in China. A multiple regression model analysis was carried out to analyze the survey data and validate the hypotheses.

The results reveal that both CSR and innovation have a U-shaped impact on the price-to-book ratio of a construction firm, a specific CFP measure. CFCP negatively moderates the U-shaped relationship between CSR and CFP, but positively moderates the U-shaped relationship between innovation and CFP.

This study goes beyond a simple linear view, instead of unveiling the nonlinear U-shaped effects of CSR and innovation on CFP that deepen the understanding of their complex relationships in the construction industry and makes construction firms aware that CSR and innovation can only improve performance if they reach a certain level. The moderating role of CFCP provides important implications for construction firms seeking to adopt appropriate competitive strategies related to social responsibility and innovation that both promote CFP and achieve sustainable development.

The purpose of this study is to solve two unique but difficult partial differential equations: the foam drainage equation and the nonlinear time-fractional fisher’s equation. Through our methods, we aim to provide accurate solutions and gain a deeper understanding of the intricate behaviors exhibited by these systems.

In this study, we use a dual technique that combines the Aboodh residual power series method and the Aboodh transform iteration method, both of which are combined with the Caputo operator.

We develop exact and efficient solutions by merging these unique methodologies. Our results, presented through illustrative figures and data, demonstrate the efficacy and versatility of the Aboodh methods in tackling such complex mathematical models.

Owing to their fractional derivatives and nonlinear behavior, these equations are crucial in modeling complex processes and confront analytical complications in various scientific and engineering contexts.

The research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.

This study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.

This study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.

This research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

This research aims to empirically investigate the impacts of product and international diversification strategies on firm-level inventory performance.

This study empirically examines the associations between product and international diversification strategies and inventory performance based on a sample of 64,124 observations across 7,367 US publicly traded firms between 1989 and 2019 from the COMPUSTAT Segment, Fundamental Annual and Fundamental Quarterly data files. We employ both linear and nonlinear regression models to perform our empirical analysis.

This research provides strong evidence that there exists a U-shaped relationship between unrelated product diversification and inventory level and a partially inverted U-shaped relationship between international diversification and inventory level. We also find a positive impact of related product diversification on inventory level, but there is no significant curvilinear relationship between related product diversification and inventory level.

Our research findings offer important insights into top management’s strategic planning for diversification strategies and operations manager’s inventory control policies to achieve the strategic fit between corporate diversification and inventory management.

Product and international diversification strategies not only play an essential role in the firm’s competitive advantage, but also have a significant influence on operations manager’s inventory decision. This research is among the first to systematically investigate how top management’s related product, unrelated product and international diversification strategies may have complex nonlinear impacts on inventory performance.