Empirical Test Research Articles

Entrepreneurial spirit: A catalyst on the road to green and sustainable development——A theoretical analysis based on dynamic games and empirical tests from Chinese data

Environmental protection and sustainable development are now profoundly ingrained in the public consciousness in the modern era of the global green revolution. First, this paper uses an evolutionary game model to theoretically analyse the impact of environmental regulation and green finance on enterprises by dissecting the game behaviour between local governments, banks and enterprises. Then, we incorporate entrepreneurial spirit into the model to determine whether entrepreneurial spirit accelerates the achievement of green sustainability objectives. Environmental regulation and green finance are found to contribute substantially to the innovation of green technologies by local enterprises, while entrepreneurial spirit accelerates this process. Finally, we empirically test the findings based on a prefecture-level panel dataset from 2007 to 2020. We find that green finance has a positive impact in Central and Western cities of China, while Eastern cities are in greater need for government environmental regulation controls. For entrepreneurial spirit, the incentive effect of entrepreneurial spirit on the level of green technology innovation is more significant in Central and Western regions of China. This paper enriches the field of research on entrepreneurial spirit and regional green sustainable development by providing empirical evidence for the evaluation of environmental regulatory and green financing policy impacts.

The robustness mechanism of the rural social-ecological system in response to the impact of urbanization——Evidence from irrigation commons in China

Urbanization is essential for achieving rapid development. In this process, the labor outmigration from rural areas to cities caused by urbanization has diversified the impacts on the robustness of the rural social-ecological system. However, existing research has rarely discussed the internal mechanism of the response of the rural social-ecological system to the impact of urbanization. Based on the coupled infrastructure systems framework, in this paper, the internal interactions of the rural social-ecological system responding to the impact of urbanization are discussed. An empirical test is conducted using survey data from 123 villages of 14 Chinese provinces. Focusing on the specific practice of China, this paper further discusses how the robustness of the rural social-ecological system can be ensured under external impact. The main conclusions are as follows: under the impact of urbanization, the internal interaction paths with which the rural social-ecological system maintains robustness at the operational level are not unique. These different internal interaction paths may not only make the rural social-ecological system automatically realize a virtuous and robust cycle under the impact of urbanization, they may also cause a gradual collapse of the rural social-ecological system. Further, the discussion of China’s specific practice shows that it is key to provide institutional rules to guarantee the operational processes through the collective-choice process, thus ensuring the robustness of the rural social-ecological system under the impact of urbanization. The inspection of the interaction mechanisms in this study may obtain some restricted views on the general laws that may be contained in the complex interaction within the rural social-ecological system, and provide a theoretical basis developing countries can apply to realize rural revitalization when faced with the irreversible wave of urbanization.

How does network structural embedding stimulate the ability of regional green technology innovation: a case study of Hubei province

ABSTRACT Green Technology Innovation (GTI) is widely acknowledged as a pivotal strategy that harmonises economic development and environmental preservation. In parallel, innovation networks have emerged as potent mechanisms empowering regional innovation. Therefore, a pivotal regarding the advancement of GTI revolves around the strategic utilisation of network embedding to foster its development. However, existing research has not provided a comprehensive analysis of the mechanism. Our study leverages both Network Embedding Theory and Game Theory to construct a game model of enterprise GTI under NSE scenarios. Then, utilising Hubei Province as a sample, we undertake empirical testing by using both a negative binomial regression model and a non-equilibrium threshold effect model. The findings suggest that NSE plays a substantial role in augmenting regional GTI, and this effect can be further magnified by the scale of regional enterprises and the level of R&D funding. Across various threshold intervals of NSE, its positive feedback effect exhibits fluctuations. However, it serves to alleviate the hindrances posed by the scale of regional enterprises to GTI and enhances the efficacy of R&D funding utilisation. The results enrich the research of NSE theory in urban GTI, and have important management significance for the formulation of GTI policies globally.

The Impact of Corporate Social Responsibility Implementation on Enterprises’ Financial Performance—Evidence from Chinese Listed Companies

Along with the constant changes in the current business environment, more and more enterprises have recognised the importance of Corporate Social Responsibility (CSR). Considering that profit maximisation is the eternal pursuit of enterprises and that some studies have already linked the financial performance of enterprises and their implementation of social responsibility together, this study will try to further explore the impact of social responsibility initiatives on enterprises’ financial performance within the context of emerging economy. Given that enterprises’ sustainable development is closely related to their implementation of CSR, an improvement in their corresponding financial performance due to effective social responsibility practices can incentivise enterprises to take part in CSR initiatives aimed at enhancing the sustainable development of society and the environment. Through using the panel data from Chinese Listed Companies, this research finds that responsibility’s implementation is positively related with enterprises’ financial performance, and that relationship is non-linear. Additionally, as a critical regulatory institution, government fails to function as a mediator within the above-mentioned relationship based on the robust empirical test. At the same time, the fulfilment of CSR can not be achieved at the expense of profit maximisation. The non-linear relationship between CSR and enterprises’ financial performance (CFP) demonstrated in this research suggests that the financial performance of a firm can be optimised when it moderately fulfils its social responsibility. This finding offers a potential optimal strategy for the sustainable development of the firm as well as society. Also, the role of government deserves further exploration and utilisation, considering its significant linkages with enterprises and social development.

Towards customer-centric sustainability: how mindful advertising influences mindful consumption behaviour

PurposeThough there is consensus that mindfulness induces mindful consumption (MC), empirical testing is needed to uncover the mechanism underlying temperance behaviour in the MC model proposed by Sheth et al. (2011). The role of mindful advertising in influencing MC needs deeper investigation. The purpose of this research paper is to bridge the gap.Design/methodology/approachThe relationship between mindfulness and temperance in consumption was investigated using an online simulation. Mindful advertising by Patagonia, with a message to buy less yet demand organic, fair-trade and recycled products, was introduced as a moderator in experimental group one. The second group was exposed to an aspirational advertisement of Tommy Hilfiger, symbolic of consumption-driving communication.FindingsNot buying any brands was the uppermost preference by the participants followed by Patagonia, which used a mindful advertisement. Tommy Hilfiger was a distant third despite using an aspirational advertisement. A predictive relationship between mindfulness and temperance in consumption remained elusive.Practical implicationsConsumer purchase decisions favouring mindfully advertised Patagonia make a strong business case for nurturing a mindful mindset and promoting mindful behaviour. The customer-centric sustainability strategy of caring for the people and the planet beforehand should take precedence over corporate social responsibility which is usually an afterthought.Originality/valueMeasuring mindfulness and MC, two constructs combined in one experimental design, using a simulation built around real-life marketing communication distinguishes this research paper.

Explicit model predictive control of magnetorheological suspension for all-terrain vehicles with road preview

The integration of magnetorheological (MR) semi-active suspension systems in all-terrain vehicles (ATV) has garnered significant attention due to their ability to enhance damping performance and off-road capabilities. However, traditional control strategies result in poor control accuracy and limited vibration reduction effects when facing complex road excitations and impact disturbances. With technological advancements, enhanced vehicle environmental perception and road sensing capabilities have made it possible to implement model predictive control (MPC) for vehicle suspensions. Nevertheless, traditional MPC is limited in vehicle suspension applications due to its high computational complexity. To address these issues, this study introduces an explicit model predictive control based on road preview (EMPC-P). Firstly, road data obtained through a non-contact measurement method enables the system to perceive road excitation information in advance. Subsequently, a 7 Degree-of-Freedom (7-DOF) suspension model incorporating road excitations is constructed. By adhering to system constraints and employing a multiparameter optimization method, the control problem based on rolling optimization is transformed into an explicit polyhedral system. The offline precomputation of control state relations enhances the computational efficiency of the control system. Through this approach, the designed EMPC allows the vehicle suspension system to make optimal control decisions quickly and accurately in response to complex driving conditions, thus improving the damping effect of the system. Through a combined approach of simulation and experimental validation, the designed EMPC-P controller is compared with the Skyhook controller under preview and non-preview states, respectively. Empirical testing confirms that the EMPC-P exhibits superior damping effects, significantly improving vehicle ride comfort and handling stability.

Resilience Capability of Indigenous People Affected by Small-Scale Gold Mining Activities: A Prevention Approach

This research addresses three main review points related to the harmful practices of artisanal and small-scale gold mining and the appropriateness of prevention approaches to resilience for local residents’ environments. First, the focus is on cases of illegal mining exploitation in North Rarowatu and Lantari Jaya, with emphasis on the aspects of disaster risk management and prevention approaches in construction areas. Second, focus is given to the abundance of gold grains in the mining area, which attracts the author to utilize a dynamic system approach to explore whether a progressive restructuring exists for avoiding casualties in the mining area. Third, the precautionary accuracy of the security forces and the government are given focus to emphasize the prohibition of mercury absorption as a mining method. This research utilizes a system dynamics methodology to investigate the review of preventive approaches for maintaining the resilience of local communities and the determinants of small-scale gold mining activities by considering other empirical testing models. This study finds that a 30–50% increase in gold production significantly results in hydrological pollution due to mercury content, increased worker deaths, and unending damage to resident ecosystems, with minimal preventive capabilities in the pre-illegal artisanal and small-scale gold mining period. Moreover, this study offers an input and output prevention approach to controlling the number of illegal gold miners while protecting the environmental resilience of local residents.

Digital economy, industrial structure upgrading, and residents' consumption: Empirical evidence from prefecture-level cities in China

In the context of promoting high-quality economic development, how to use digital technology to empower industrial transformation and upgrading, and then drive consumption growth, has become a critical issue that needs to be solved urgently. Based on the panel data of prefecture-level cities in China from 2011 to 2020, this paper has discussed the influence of the digital economy on residents' consumption and its internal mechanism. Theoretical analysis and empirical test results show that, firstly, the digital economy has a positive effect on residents' consumption, and this conclusion is still valid after the endogenous test and robustness test. Secondly, mechanism analysis results confirm that industrial structure upgrading is the main channel through which the positive mediating effect operates. Thirdly, the influence of the digital economy is only valid for rural areas rather than urban areas, and more significant for western regions than eastern and central regions, which indicates the development of the digital economy is beneficial to narrowing the consumption gap. Finally, the positive impact of the digital economy on residents' consumption is continuously strengthened with the upgrading of industrial structure, which is a significant non-linear characteristic of the marginal effect increasing. The above research conclusions can provide a theoretical basis for further improving the infrastructure of the digital economy, accelerating the integration of the digital economy with traditional industries, and building a consumer Internet.

Does trade freedom affect exchange rate movement? A perspective of high-technology trade

Changes in the degree of trade freedom influence economic development and foreign investment, which in turn, affect currency values and exchange rate movements. Therefore, this study examined the direct and indirect impacts of trade freedom on exchange rate movement in emerging, developing, and developed economies. Empirical tests conducted using panel data from 75 countries revealed that trade freedom has a nonlinear U-shaped relationship with exchange rate movement, which is positively moderated by high-technology trade and foreign direct investment. Additionally, the results of heterogeneity analysis showed that trade freedom has a linear positive impact on the exchange rate movement of developed economies but a U-shaped impact on emerging and developing economies, with a stronger impact on emerging economies. The findings of this study provide valuable insights for governments to strike a balance between promoting trade freedom and maintaining currency exchange rate stability.

The path from root input to mineral-associated soil carbon is dictated by habitat-specific microbial traits and soil moisture

Soil microorganisms help transform plant inputs into mineral-associated soil organic carbon (SOC) – the largest and slowest-cycling pool of organic carbon on land. However, the microbial traits that influence this process are widely debated. While current theory and biogeochemical models have settled on carbon-use efficiency (CUE) and growth rate as positive predictors of mineral-associated SOC, empirical tests are sparse, with contradictory observations. Using 13C-labeling of an annual grass (Avena barbata) under two moisture regimes, we found that microbial traits associated with formation of 13C-mineral-associated SOC varied by soil habitat, as did active microbial taxa and SOC chemical composition. In the rhizosphere, bacterial-dominated communities with fast growth, high biomass, and high extracellular polymeric substance (EPS) production were positively associated with 13C-mineral-associated SOC. In contrast, the detritusphere held communities dominated by fungi and more filamentous bacteria, and with greater exoenzyme activity; there, 13C-mineral-associated SOC was associated with slower microbial growth and lower microbial biomass. CUE was a negative predictor of 13C-mineral-associated SOC in both habitats. Using 13C-quantitative stable isotope probing, we found that the majority of 13C assimilation in the rhizosphere and detritusphere at week 12 of the experiment was performed by very few bacterial and fungal taxa (3–5% of the total taxa that assimilated 13C). Several complementary chemical analyses (13C-NMR, FTICR-MS, and STXM-NEXAFS) suggested that SOC in the rhizosphere had a more oxidized chemical signature, while SOC in the detritusphere had a less oxidized, more lignin-like chemical signature. Our findings challenge current theory by demonstrating that microbial traits linked with mineral-associated SOC are not universal, but vary with soil habitat and moisture conditions, and are shaped by a small number of active taxa. Emerging SOC models that explicitly reflect these interactions may better predict SOC storage, since climate change causes shifts in soil moisture regimes and the ratio of living versus decaying roots.

A simulation and experimental verification of the operation of the oxidising catalytic converter in diesel engine.

This paper investigates an oxidizing catalytic converter in a diesel engine's particulate filter system, focusing on simulations and empirical studies. The converter, with a 1.4 dm3 volume and 400 cpsi channel density, features a platinum coating of 2.5 g/dm3. Scanning electron microscopy (SEM) examined its surface, revealing platinum and a highly porous structure with randomly distributed Pt crystallites. Simulations were conducted using AVL Boost, utilizing real exhaust gas concentrations to assess various converter volumes and channel densities for CO, HC, and NO2 conversion in NOX. These simulations were paralleled with empirical tests on an engine dynamometer. The comparison of simulation and experimental data showed that the simulation algorithm could accurately predict the converter's performance in reducing CO and HC levels and NO2 in NOX. This suggests that simulations can partly replace costly empirical research, offering a preliminary evaluation of the converter's future effectiveness.

Stochastic Arbitrage Opportunities: Set Estimation and Statistical Testing

We provide a formal statistical theory of consistent estimation of the set of all arbitrage portfolios that meet the description of being a stochastic arbitrage opportunity. Two empirical likelihood ratio tests are developed: one for the null that a given arbitrage portfolio is qualified, and another for the alternative that the portfolio is not qualified. Apart from considering generalized concepts and hypotheses based on multiple host portfolios, the statistical assumption framework is also more general than in earlier studies that focused on special cases with a single benchmark portfolio. Various extensions and generalizations of the theory are discussed. A Monte Carlo simulation study shows promising statistical size and power properties for testing the null, for representative data dimensions. The results of an empirical application illustrate the importance of selecting a proper blocking structure and moment estimation method.

Carbon emissions prediction based on the GIOWA combination forecasting model: A case study of China

Mitigating greenhouse gas emissions is a significant global challenge, and precise prediction of carbon emissions holds the utmost importance for China to attain its dual carbon goal. To overcome the limitations of existing studies using a single forecasting method, based on quadratic exponential smoothing, multiple linear regression, and Gaussian process regression models, this paper constructs a carbon emission combination forecasting model with the generalized induced ordered weighted average (GIOWA) operator and analyzes carbon emission reduction performance. Empirical testing utilizing China's carbon emission data from 1980 to 2020 reveals the following findings: (1) The GIOWA combination forecasting model significantly enhances the accuracy of carbon emission forecasts, with an average accuracy exceeding 99.5% over the sample period, surpassing various single forecasting methods. (2) The carbon emission reduction target can be achieved under three different scenarios of low, average, and high GDP growth rates. Specifically, under the low growth rate scenario, China can achieve a 60% reduction in carbon intensity by 2025 and a 65% reduction by 2030. This study offers valuable decision support for the development of effective carbon reduction policies.

Analyzing energy intensity of Indian Chemical industry: A panel data approach

The chemical industry is directly or indirectly connected with almost every industrial process and holds a crucial place in the economic and social advancement of India. At the same time it is however, the second highest energy intensive industry in the country. Thus, we attempt to look into the factors that affect the energy intensity of Indian chemical industry. We collect a panel dataset including a total of 2613 chemical firms for the period 2010 to 2021 for our analysis. We carry out our empirical testing under both linear and non-linear framework by employing fixed effect regression and panel quantile regression methods respectively.We find that energy intensity for the sample chemical firms increases due to poor labour productivity, huge plant and machinery, outsourcing operations, and more use of IT-enabled services. On the other hand, use of better quality raw material and advanced technology can help optimising the energy intensity. We also discover that profitable firms and firms larger in size are energy efficient. Based on the findings, we suggest professional training programs and vocational skill development programs for enhancing labour productivity. Profitable firms are suggested to invest in technological up-gradation and energy saving technology. We believe the findings of the study can provide a portfolio of variables to the managers and policy makers in order to diversify their attention to find all possible ways to reduce energy intensity of the Indian chemical firms.

Maternal relative income, bargaining power, and children's education expenditure

This study presents a household bargaining model to theoretically examine the logical mechanisms by which maternal relative income influences children's education expenditure. The theoretical findings demonstrate that an increase in maternal relative income can enhance children's investment in education through both the income effect and bargaining effect. To validate the theoretical model, empirical tests are conducted using panel data from the China Family Panel Studies (CFPS) covering the period from 2010 to 2018. The findings demonstrate a significant and robust positive influence of maternal relative income on children's education expenditure, even after conducting rigorous robustness tests and addressing potential endogeneity issues. Heterogeneity analysis reveals that the increase in maternal relative income particularly benefits boys, younger children, and those with fewer siblings. Moreover, households residing in northern China and high-income households observe a more substantial rise in their children's education expenditure as a result of an increase in maternal relative income. Mechanism tests indicate that the impact of maternal relative income on children's education expenditure primarily stems from both the income effect and bargaining effect.

Low-carbon cities pilot and industrial structure upgrading: enabling or negative? Evidence from a quasi-natural experiment in China

The enhancement of industrial structural refinement stands as a pivotal approach to harmonize high-quality economic development and environmental preservation. In this study, we seek to assess the impact of low-carbon city pilot programs on the upgrading of industrial structure. Leveraging panel data encompassing 283 prefecture-level cities in China from 2006 to 2019, this study undertakes an empirical test employing the time-varying difference in difference (DID) methodology. We further delve into an examination of the specific mechanisms and heterogeneity of effects. The findings are summarized as follows: (1) the low-carbon cities pilot significantly promoted the supererogation of industrial structure, but did not promote the rationalization of industrial structure. This observation remains valid even after undergoing a battery of robustness tests. (2) The pilot propels the upgrading of industrial structure by fostering green technology innovation and diminishing resource dependence. Local government support positively moderates the effect of green technology innovation on industrial structure supererogation, while negatively moderating the effect of green technology innovation on industrial structure rationalization. Further tests reveal that local government support can positively moderate the mediating effect of green technology innovation. (3) The policy effect of the pilot is more conspicuous in the eastern region, which is mainly achieved via increasing the intensity of green technology innovation and reducing resource dependence. (4) The pilot exhibits a more pronounced driving effect on the industrial structure of high-level cities, primarily through the promotion of green technology innovation. These findings not only provide empirical evidence for the industry-driven effect of low-carbon cities, enriching the effect assessment research of low-carbon city pilot policies from the theoretical level, but also furnish policy reference for realizing the green and high-quality economic development of low-carbon cities from the practical perspective.

Digital inclusive finance: A lever for SME financing?

This paper systematically investigates the relationship between digital inclusive finance and small and medium enterprises (SMEs) financing constraints. We extrapolate the influence model between them from an economic theory perspective and conduct an empirical test using two-way fixed effects and a mediation effect model. The results show: (1) Digital inclusive finance significantly alleviates the financing constraints of SMEs; (2) Compared to the breadth of coverage, the depth of use of digital inclusive finance has a more noticeable effect; (3) The alleviation effect of digital inclusive finance exhibits heterogeneity. It can correct the attribute mismatch, field mismatch, and regional mismatch of traditional financial loan services; (4) Digital inclusive finance alleviates SME financing constraints by reducing financing costs and controlling leverage levels, increasing internal sources of enterprise funds. This research is significant for promoting digital inclusive finance to alleviate the financing difficulties of SMEs in China and provides valuable solutions for other countries to mitigate the “Macmillan Gap” phenomenon.

How does the digital economy affect urban CO2 emissions? Mechanism discussion and empirical test

How does the digital economy affect urban CO2 emissions? Mechanism discussion and empirical test

How Authoritarian Regimes Use Organizations to Solidify Control: A Theory of Pro-Forma Cooptation and an Empirical Test from Reappointments to Congress in China

We know that, through lobbying and contributions, organizations systematically seek to influence political outcomes in liberal democracies. But what role do organizations play in an authoritarian regime’s strategy for remaining in power? We argue that in order to maintain stability and consolidate control, an authoritarian regime must actively work to preempt dissent and the emergence of oppositional challengers. When potential challengers are unknown ex ante, the best guess is that they may rise from the ranks of those who run economically powerful organizations. Ability to control these organizations then minimizes the risk of instability. One way in which the regime accomplishes this control is through pro-forma cooptation—the process by which organizational leaders are assigned to positions with nominal authority in the government, thus ensuring their allegiance. We develop a theory predicting which organizations will be targeted for cooptation and posit that absolute and relative size and industry context are the key determinants. Empirical analyses of reappointment to congress of senior business executives in China offer support for the theory. The findings also offer a way to think of cooptation that is different from the conventional view that it drives adaptation (because power sharing widens representation and vested interests). By contrast, pro-forma cooptation of prominent organizations under authoritarian rule reifies the regime’s dominance and solidifies its control, thus promoting inertia through the reproducibility of hierarchy in the social structure.

Can smart cities reduce labor misallocation? Evidence from China

The marketization of factors in China lags behind that of products, and this lag is directly manifested as insufficient effective supply of labor, rising labor costs of enterprises, and serious distortion of labor resource allocation, which to a great extent restricts the economic transformation from “quantity” to the “quality” growth. The labor allocation effect of smart cities plays an important role in promoting the transformation to high-quality development in China, but there is still a lack of empirical research testing this effect. Based on panel data of 151 cities at the prefecture level and above for the period 2006–2018, this paper uses a DID model to evaluate the impact of smart city pilot projects on labor misallocation. The results show that, first, smart cities can significantly reduce labor misallocation, and this finding holds under a series of robustness tests. Second, smart cities can reduce labor misallocation through the formation of industrial agglomeration and the upgrading of the industrial structure. Third, the effect of smart cities was more significant in central and eastern cities and large-scale cities than in western cities and small and medium-scale cities. Fourth, smart cities have a significant spatial spillover effect on the reduction of labor misallocation.