Nonlinear Perspective Research Articles

The role of financial drivers on regional economic resilience: Does information technology level matter?

<p>Economic globalization has intensified economic volatility around the world, and the importance of economic resilience has become increasingly prominent in the face of rising uncertainty due to frequent domestic and foreign shocks. Based on provincial panel data in China from 2008-2019, a comprehensive indicator system is constructed to measure regional economic resilience (RER), and the impact of financial driver (FD) on RER is explored from staged, pathway and non-linear perspectives. The main findings are as follows. (1) Both national and regional levels of FD and RER show an upward trend, and the impact of FD on RER has an “inverted-U” shape: as the capacity of FD increases, its impact on regional economic resilience shifts from promoting to inhibiting. The RER has significant spatial agglomeration characteristic. (2) Interestingly, staged analysis shows FD can significantly promote RER only when it is in the “recovery stage”. (3) The pathway analysis of its effect on regional economic resilience shows the following characteristics: financial scale > financial efficiency > financial deepening. (4) From different regions, there are significant differences in the effect of FD on the promotion of regional economic resilience: central region > western region > eastern region. Finally, the corresponding suggestions were provided.</p>

The effect of social media influencer marketing on sustainable food purchase: Perspectives from multi-group SEM and ANN analysis

This study examines the impact of social media influencers' (SMIs) intimate self-disclosure, environmental concern, and spending self-control on consumers' sustainable food purchase intention and explores the mediating effect of consumption value. It ranks the relative importance of these factors and measures generational differences on the impact of SMIs. Data from 628 respondents obtained via an online survey was analyzed using a dual-stage multi-group structural equation model (SEM) and artificial neural network (ANN) techniques. The SEM revealed that SMIs' intimate self-disclosure, environmental concern, and spending self-control positively affected sustainable food purchase intention by mediating social and epistemic values. A multi-group analysis of the SEM found no significant generational differences. The ANN indicated that consumer purchases of sustainable food were primarily associated with SMIs’ spending self-control followed by their environmental concern. The ANN predicted consumer sustainable food purchase intention with 99.4% accuracy. Theoretically, this study enhances the knowledge of how consumers internalize social media influencer marketing (SMIM) and encourages their endorsement of sustainable foods by introducing TCV into the SOR framework. It also refutes the view that SMIs are significant only for younger generations and reveals the relative importance of SMIs impact factors from a non-linear perspective. From a practical perspective, we offer a specific SMIM investment strategy to maximize consumers' sustainable food purchases and several persuasive strategies for SMIs as opinion leaders. From a societal perspective, this research promotes sustainable development, human health, and a sustainable food economy.

The evolutionary process of the development path of cultural tourism industry integration from a non-linear perspective

Abstract The cultural tourism industry and the tourism industry are both different and interrelated, and both are the most promising industries in the modern service industry. Along with the continuous socio-economic development, the influential role of cultural values is expanding and is an inevitable and positive industrial development trend. The globalization of the economy, changes in transportation and information technology, and the widespread use of the Internet have brought about a continuous increase in tourist demand, an essential change in the relationship between all relevant stakeholders in the cultural tourism industry, and an increasing complexity of development. The traditional linear approach to analyzing the components of the system ignores the complexity and dynamics of the cultural tourism industry, and it is difficult to adapt to the development practice. The results show that: after a major national public health outbreak of SARS at the end of 2002, the number of tourism receivers in Shanghai grew -by 13.11%; the number of tourism receivers in Shanghai grew by 24.82% with the bid for the Chinese Olympic Games in 2008, and the evolution of Shanghai’s cultural and tourism industry system has the characteristics of a small world and an approximate scale-free network, which behaves as a chaotic deterministic nonlinear dynamical system; the integration of Shanghai’s cultural and tourism industry follows “orderly - chaotic edge - emergent - new orderly”, the process of jumping up from low-level orderly to high-level orderly evolution; This paper provides a precise analysis of the evolutionary path of the cultural tourism industry, which effectively assists cultural tourism industry managers in adaptive management and regulation by providing methodological and technical support.

Impacts of Digital Economy on Urban Entrepreneurial Competencies: A Spatial and Nonlinear Perspective

The vigorous rise of the digital economy not only affects the dynamic system and development path of entrepreneurial activities, but also brings new opportunities to enhance urban entrepreneurial competencies. The purpose of this paper is to investigate whether the digital economy supported by digital technologies can become a new kinetic energy that can enhance urban entrepreneurial competencies in the context of the “New Normal”. Based on the sample of 286 cities in China, this paper investigates the temporal and spatial characteristics of urban entrepreneurial competencies and analyzes the spatial effect of the digital economy on urban entrepreneurial competencies using the spatial dynamic panel Durbin model. Furthermore, this paper examines whether the impact of the digital economy on urban entrepreneurial competencies has a “threshold effect” in different business environments by using threshold spatial dynamic panel model. It is found that: (1) Urban entrepreneurial competencies have obvious spatial dependence; (2) The digital economy harms the entrepreneurial competencies of neighboring cities; (3) In different business environments, the impact of the digital economy on urban entrepreneurial competencies shows obvious non-linear characteristics.

A new approach to assessing natural capital consumption inequities from a nonlinear perspective

The rate of decline in ecosystem services has been exacerbated by inefficient and inequitable natural resource use and management. This study analyzes the natural capital stock and outflow in the Arid and Semi-Arid Northern Region of China (ASRNC) from 2000 to 2020. The Gini coefficient and coefficient of variation are used in the equity assessment of natural capital consumption. Over-appropriation of natural capital is a prerequisite for the inequitable distribution of natural resources, and all variables were accounted for through a geographic probe. Since most of the variables in this study have a nonlinear relationship, an in-depth analysis was conducted using NARDL. The results show that (1) natural capital flow occupancy generally shows an upward and downward trend and peaks in 2015. Natural capital stock occupancy was on a linear upward trend over the study period, rising from 14.580hm2/cap to 18.272hm2/cap. Depletion of natural capital is increasing and construction land has become the land type that leads to deep footprint changes (2) A city's consumption of natural capital matches its ecological carrying capacity to contribute to economic growth. However, the Gini coefficient for the depth of the ecological footprint from 2000 to 2020 is on a fluctuating upward trend. It reached its maximum in 2020 (1.457), indicating that the inequitable use of natural capital stock is increasing. (3) In the long run, population density and urbanization rate have different adverse effects on utilizing natural capital stock. In addition, the equity of planted forest area on natural capital use is heterogeneous in the long and short term. There is a negative effect of planted forest area on natural capital stock under long-term development. The study helps to judge the equity of regional consumption of natural capital and provides a scientific basis for the harmonious development between socio-economic systems and ecosystems.

Examining the Effect of Privatization on Renewable Energy Consumption in the Digital Economy under Economic Patriotism: A Nonlinear Perspective

This study is an effort to investigate the asymmetric effects of privatization and the digital economy on renewable energy consumption. The nonlinear quantile autoregressive distributed lag (QARDL) technique is used to estimate short and long-run analysis. Findings of the nonlinear QARDL model posit that the long-run positive shock in privatization promotes renewable energy consumption by increasing renewable energy consumption, while the long-run negative shock in privatization demotes renewable energy consumption by reducing renewable energy consumption. In the short run, the positive shock of privatization does not significantly impact renewable energy consumption, while the negative shock of privatization reduces renewable energy consumption. Moreover, information and communications technology (ICT), economic development, and financial development increase renewable energy consumption in the long run; however, in the short-run only financial development helps increase renewable energy consumption. The Wald test confirms the asymmetric impact of privatization on renewable energy consumption only in the long run. Based on these results, policymakers should thus take into account both positive and negative shocks in privatization when developing policies to encourage pro-environmental behavior.

Non-Linearity and Feature-Based Phonotactics of Khasibi Arabic Syllable Templates: A Phonological Survey

This paper is intended to explore the study of permissible orders of Khasibi segments in formatting syllable templates (phonotactics). The treatment of phonotactic rules and representations of Khasibi syllables is touched on by means of two influential factors. One of them is the non-linear perspective that is used to cover the hierarchal mapping of the syllables. The other is greater exploitation of the theory of distinctive features to elucidate the phonetic properties of the sound segments of which the syllables are made up. The overall phonontactic scene of Khasibi Arabic is thus integrated by double phonological instruments to attain some sort of comprehensiveness and universality and simultaneously to manifest a degree of idiosyncrasy. Different results are objectively reached, and the most noteworthy one is that two X-position consonants (consonantal clusters) are formed uniquely whereby certain phonological phenomena like geminates and ambi-syllabicity are directly responsible for such a formation.

Does green technology innovation reduce anthropogenic PM2.5 emissions? Evidence from China's cities

Quantitatively analyzing the role of green technology innovation's influence on anthropogenic PM2.5 emission is important for the government to implement policies to control pollution. Here, we analyzed regional green technology innovation's influence on PM2.5 emissions in China. The STIRPAT model and panel threshold model were performed from linear and non-linear perspectives. We collected panel data at the prefecture-level from 2006 to 2018 in China. Our results show that green technology innovation could significantly reduce PM2.5 emissions. In addition, we detected double and single threshold effects when per capita GDP and per capita education expenditure were selected as threshold variables, respectively. Our analysis indicates that regional heterogeneity and the stage of economic development and human capital levels should be involved in green-technology-driven emission control policy.

How does financial development influence carbon emission intensity in the OECD countries: Some insights from the information and communication technology perspective

Based on an extended STIRPAT framework, this paper investigates the effects of financial development on carbon emission intensity in OECD countries from linear and non-linear perspectives, where financial development is proxied by three dimensions: financial deepening, financial deepening, and financial size, and financial efficiency. Fortunately, three types of financial development significantly alleviate carbon emission intensity. An extended moderation effect model is built to estimate the effect of financial development via information and communication technology on carbon emission intensity. The results reveal that internet-based information and communication technology and service-based information and communication technology are positively correlated with carbon emission intensity. To effectively handle the endogeneity issue triggered by causal relationships between variables and allow potential non-linear nexus, an advanced dynamic panel threshold model incorporating the generalised method of moments is employed to investigate how financial development affects carbon emission intensity under different types of information and communication technology. Empirical evidence demonstrates the significance of the non-linear nexus between financial development and carbon emission intensity. Lastly, heterogeneity analysis demonstrates the existence of heterogeneity associated with institutional quality, degree of economic development, and resource endowment concerning the effect of financial development on carbon emission intensity among the OECD countries.

The interrelationship between bank capital and liquidity creation: A non-linear perspective from the Asia-Pacific region

The study investigates nonlinearity in the interrelationship between liquidity creation (LC) and bank capital. It addresses the reverse-causality concerns by employing a simultaneous equations model with a two-step system GMM estimator. The data comprises 597 commercial banks in the Asia-Pacific region from 2006 to 2019. The findings indicate a U-shaped bi-directional relationship between bank capital and LC, with a significant moderating effect of bank size. The results also hold for Advanced economies (AEs), Basel II and Basel III periods. However, there is an inverted U-shaped impact of capital on LC in the Emerging market and developing economies (EMDEs). The findings call for coordination between liquidity and capital regulations. Further, policymakers should adopt a tailored regulatory approach for banks instead of uniform blanket regulations, as the latter might prove to be counterproductive.

The Relationship between Corporate Social Responsibility and Firm Value of Chinese Firms: Exploring from Degree of Internationalization.

The purpose of this paper is to explore the relationship between corporate social responsibility (CSR) and firm value in the Chinese market and identify factors that may influence it. We discuss the relationship between CSR engagement in Chinese firms and firm value from a nonlinear perspective. In addition, we examine how the degree of internationalization in a firm may affect the relationship between CSR and firm value. We employ the Hausman test to compare a random-effects and a fixed-effects model, and after testing and comparison, the fixed-effects model was chosen in our paper. Using data from 314 firms listed in China's A-shares market from 2010 to 2017, we verify the U-shaped relationship between CSR and firm value. Meanwhile, the degree of internationalization will affect firm value but cannot positively regulate the relationship between corporate social responsibility and firm value.

A Study on the Spatial Correlation Effects of Digital Economy Development in China from a Non-Linear Perspective

Accurate analysis of the spatial correlation effects, spatial aggregation patterns, and critical factors in the development of China’s digital economy is of great significance to the high-quality development of China’s economy. Based on the monthly data of “The Tencent Internet Plus” digital economy index for 31 provinces in China from 2018 to 2020, the non-linear Granger causality test and social network analysis were applied to reveal the spatial correlation effects of China’s digital economy. The quadratic assignment procedure (QAP) was used to empirically examine the factors influencing the formation of non-linear spatial association networks. The results show that the spatially linked relationships of the digital economy in 31 Chinese provinces exhibit a significant non-linear spatially correlated network structure. Block model analysis reveals that the development of the digital economy between the four major sectors is closely linked, and the national linkage effect is significant. The results of the secondary assignment procedure indicate that capital stock, information infrastructure, and geographical proximity have a significant positive impact on the formation of spatial linkages in the digital economy. In contrast, technological innovation has a significant negative impact.

Evaluation of global teleconnections in CMIP6 climate projections using complex networks

Abstract. In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections. We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height at 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective. While doing so, a number of technical tools and metrics, borrowed from different fields of data science, are implemented into the δ-MAPS framework in order to overcome specific challenges posed by our target problem. Those are trend empirical orthogonal functions (EOFs), distance correlation and distance multicorrelation, and the structural similarity index. δ-MAPS is a two-stage algorithm. In the first place, it assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct 2 unipartite and 1 bipartite network for 22 historical CMIP6 climate projections and 2 century-long coupled reanalyses (CERA-20C and 20CRv3). Potential non-stationarity is taken into account by the use of moving time windows. The networks derived from projection data are compared to those from reanalyses. Our results indicate that no single climate projection outperforms all others in every aspect of the evaluation. But there are indeed models which tend to perform better/worse in many aspects. Differences in model performance are generally low within the geopotential height unipartite networks but higher in sea surface temperature and most pronounced in the bipartite network representing the interaction between ocean and atmosphere.

Detecting the hidden asymmetric relationship between crude oil and the US dollar: A novel neural Granger causality method

The relationship between financial series is not always easy to detect due to their underlying asymmetry and nonlinearity. Both characteristics are not usually considered simultaneously, which may lead to many drawbacks in financial analysis. Hence, we develop a novel neural Granger causality method from both asymmetric and nonlinear perspectives and further revisit the response and impact of crude oil on the exchange rate. Our findings reveal the unidirectional nonlinear and asymmetric effect of crude oil on the exchange rate; that is, positive and negative oil prices can have a substantial impact on exchange rate shocks. Interestingly, this influence seems to strengthen after the Russia–Ukraine conflict. Besides, we also use simulation technology to evaluate the rationality and effectiveness of our proposed methods. Investors, policymakers, and scholars may be interested in our findings regarding the oil-dollar relationships; as well as interested in applying our methodology to other contexts.

Nonlinear aeroelastic modeling and comparative studies of three degree of freedom wing-based systems

The effects of structural and aerodynamic nonlinearities are investigated on an aeroelastic system with three degrees of freedom, those being plunge, pitch, and flap motions using two different aerodynamic load representations. Stall effects are introduced using quasi-steady and unsteady aerodynamic representations. The effects of the unsteadiness of the flow and stall effects on the type of Hopf bifurcation and the limit cycle oscillations of the system are explored. A comparative study between the unsteady and quasi-steady representations from a nonlinear perspective is also carried out. Results from the linear analysis show that for this specific aeroelastic system, its linear characteristics are dependent on the aerodynamic representation and the system’s design. Additionally, the quasi-steady approximation of the aerodynamic loads results in an inaccurate prediction of the linear flutter speed. Furthermore, the nonlinear analysis shows the existence of an instability shift from the supercritical to the subcritical type, depending on the value of the stall coefficient, as well as that of the cubic nonlinearities, and is more dominantly for the case when the quasi-steady representation is considered. Results show that, even for small reduced frequencies and small angles of attack scenarios, the unsteady representation of aerodynamic loads is critical to correctly predict the flutter speed, instability type, and system’s dynamics.

Assessing non-linear effects of government size on inflation in India: recent evidence from smooth transition autoregression model

PurposeStandard economic theory predicts that any increase in public spending is accompanied by a rise in inflation in an economy. This paper presents empirical proof that prices do not always rise with an increase in public expenditure but only up to a certain threshold level. The primary aim of this paper is to unearth the government size-inflation nexus in India for the period from 1971 to 2019.Design/methodology/approachThe logistic STAR (smooth transition autoregression) model is employed to unravel the government size-inflation nexus for the Indian economy from a non-linear perspective.FindingsThe finding of our study confirm the non-linear relationship between the size of the government and inflation in India. The estimated threshold level for government size is precisely found to be 9.27%. The size of the government exerts a negative influence on inflation until it reaches the optimal or threshold level. Any further increase in the size of government beyond this threshold level would result in a rise in inflation.Research limitations/implicationsThe findings have implications for the conduct of fiscal policy. Policymakers can increase government spending in a regime of small government size without having any inflationary impacts by generating revenues from taxes and other sources instead of relying much on the central bank. In the regime of a large-sized government, adhering strictly to the discipline in the conduct of fiscal and monetary policies would help curb inflation and enhance growth synchronously, hence alleviating any loss of welfare.Originality/valueTo the best of the authors’ knowledge, this study is an attempt to revisit the government size-inflation nexus in India from a non-linear perspective using the Smooth Transition Autoregression (STAR) model for the first time.

The Thornton Wilder Encyclopedia

The Thornton Wilder Encyclopedia

How Does Manufacturing Intelligentization Influence Innovation in China from a Nonlinear Perspective and Economic Servitization Background?

Under the trend of high-quality economic development and economic servitization in China, it is of great significance to study the impact of manufacturing intelligentization on innovation and its mechanisms. This study uses a sample of 30 of China’s provinces from 2008 to 2020 to empirically test the effect of manufacturing intelligentization on innovation performance from a nonlinear perspective and examine the intermediary mechanism of diversified agglomeration of producer services against an economic servitization background. The study finds that intelligentization has a significant inverted U-shaped impact on innovation performance. It shows that the positive marginal intelligentization effect on innovation gradually decreases, and intelligence inhibits innovation when it exceeds the threshold. In addition, diversified agglomeration of producer services can improve innovation performance, and intelligentization has an inverted U-shaped effect on this diversified aggregation. Thus, the nonlinear influence of intelligence on innovation performance has a channel of diversified agglomeration of producer services. Furthermore, human capital has a reverse moderating effect on the inverted U-shaped relationship between intelligentization and innovation performance. This conclusion can help to promote the innovation-driven and sustainable development of China’s economy under the intelligent manufacturing strategy.

Impacts of green finance on green innovation: A spatial and nonlinear perspective

This paper provides an in-depth understanding of the mechanisms of green finance on green innovation, focusing on their spatial and non-linear relationships. Using panel data of 30 provinces of China during the period of 2009–2017, a green finance index is constructed, and the spatial Durbin model and panel threshold model are used. The results reveal that: (1) Green finance and green innovation had significant positive autocorrelation , and the development of green finance in provinces of central and western China were still in the lower-level range. (2) The coefficients of the direct effect and indirect effect of green finance on green innovation were significantly positive, which indicated that green finance was conducive to enhancing green innovation in local and adjacent provinces during the research period. (3) Double threshold effects of green finance on green innovation were observed, which demonstrated that the driving effect of green finance was decreased with the raising of intensity of environmental regulation. The implication of these results is that government should make full use of the radiation and trickle-down functions of green finance and green innovation to narrow regional gaps in sustainable development while maintaining a moderate intensity of environmental regulation. • A green finance index of 30 provinces of China during the period of 2009 to 2017 was constructed on the basis of green credit, green securities, green insurance, and green investment. • The heterogeneity of region and time for green finance were analyzed employing the spatial exploratory analysis, which manifested that the spatial evolution of green finance in China presents a gradient decreasing pattern from east to west. • The impact of green finance on green innovation was explored by the spatial Durbin model, which proved that the direct effect and the spatial spillover effect were significantly positive. • Moderate intensity of environmental regulation helps green finance promote green innovation and this value should not exceed a maximum of 0.935.

Visualization of occipital lobe and zygomatic arch of brain region through non-linear perspective projection using DCO algorithm

Visualization of occipital lobe and zygomatic arch of brain region through non-linear perspective projection using DCO algorithm