Search results

In typical model-based calibration, linearization errors are derived inevitably, and non-negligible negative impact will be induced on the identification results if the rotational kinematic errors are not small enough or the lengths of links are too long, which is common in the industrial cases. Thus, an accurate two-step kinematic calibration method minimizing the linearization errors is presented for a six-DoF serial robot to improve the calibration accuracy.

The negative impact of linearization on identification accuracy is minimized by removing the responsible linearized kinematic errors from the complete kinematic error model. Accordingly, the identification results of the dimension-reduced new model are accurate but not complete, so the complete kinematic error model, which achieves high identification accuracy of the rest of the error parameters, is combined with this new model to create a two-step calibration procedure capable of highly accurate identification of all the kinematic errors.

The proportions of linearization errors in measured pose errors are quantified and found to be non-negligible with the increase of rotational kinematic errors. Thus, negative impacts of linearization errors are analyzed quantitatively in different cases, providing the basis for allowed kinematic errors in the new model. Much more accurate results were obtained by using the new two-step calibration method, according to a comparison with the typical methods.

This new method achieves high accuracy with no compromise on completeness, is easy to operate and is consistent with the typical method because the second step with the new model is conveniently combined without changing the sensors or measurement instrument setup.

Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.

Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.

In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.

The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.

Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

The neo-Kaleckian model follows the ideas of Marx, Keynes and Kalecki, that investment is a key influencing factor in the dynamics of the capitalist mode of production. Through the discussion of different forms of investment decision function, this paper constructs the analysis framework of wage-led and profit-led economic growth regimes.

The model has become an important theoretical paradigm for current Western heterodox economists regarding the research on the impact of functional income distribution on economic growth, and it has a very large impact on both theoretical and empirical research. Starting from Marx's reproduction theory, this article discusses the theoretical shortcomings of the neo-Kaleckian growth regime model.

This paper mainly focuses on three aspects: (1) the ideological legacy of “Smith's Dogma”; (2) neglecting the restrictions on income distribution from the organic composition of capital and the surplus value rate; (3) technological progress and the formation of a new long economic wave.

The authors believe that the neo-Kaleckian model unilaterally emphasizes the demand-side factors in the economy and, unconsciously or not, ignores the role of the supply-side, which makes it encounter certain limitations in explaining long-term growth. Even if some empirical conclusions are employed to bridge functional income distribution and technological progress, there is still a lack of a theoretical basis for accurately describing long-term economic changes using this model. In order to better promote high-quality economic development and accelerate the formation of a new pattern of economic development in which the domestic large-scale cycle is the mainstay and the domestic and international double cycles promote each other, the authors need to adopt a policy combination with the supply-side as the main and the demand-side as the supplement, and to work from both sides.

Based on social cognitive theory, this study aims to explore the psychological mechanism behind consumer verification behavior following tourism e-commerce live-streaming.

Based on grounded theory, data were collected through 20 semi-structured in-depth interviews and analyzed.

This study identified that companies commonly use reminder messages and secondary promotions to facilitate the verification of tourism live-streaming products. Throughout this process, consumers undergo various psychologies related to verification. Specifically, they experience four positive verification psychologies: fear of missing out, anticipated emotions, status self-esteem and promotional perception. They also encounter two negative verification psychologies: psychological reactance and invasiveness. In addition, environmental factors such as the type of tourism live-streaming products and tourism destinations, along with individual trait factors like cognitive miserliness, tourism experience, autonomy, regulatory mode and impulsiveness, play significant roles in shaping verification behavior. These factors collectively influence the formation of verification behavior.

This study can provide recommendations for tourism companies to conduct marketing events following live-streaming. It is one of the earlier comprehensive studies discussing how to promote verification behavior following tourism e-commerce live-streaming. It helps to understand the psychological mechanism underlying the formation of verification behavior.

The purpose of this study is to explore the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports.

Based on the theoretical analysis of the mechanism of the digital economy’s influence on the binary margin of agricultural exports, this study empirically examines the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports based on China’s customs export data from 2011 to 2016.

The relevant findings are threefold. (1) The digital economy significantly improves the binary margin of agricultural exports, and its effect on the intensive margin is stronger than that on the expansive margin. After the expansive margin is subdivided, the effects on the three sub-variables of the expansive margin are in the following order: old products exported to new markets > new products exported to old markets > new products exported to new markets. (2) The heterogeneity analysis reveals that the digital economy has a stronger role in promoting the binary margin of exports for enterprises in the eastern region, high-income countries as the destination of exports and state-owned enterprises. (3) Mechanism analysis shows that the digital economy promotes the binary margin of agricultural exports by reducing trade costs and intensifying market competition.

First, in terms of research perspective, although there are some studies on the impact of the digital economy on export trade in existing literature, the research objects mainly focus on manufacturing enterprises. In fact, agricultural trade is susceptible to natural conditions and seasonal factors, and countries may impose more SPS measures and TBT measures on agricultural trade due to risk considerations. The relationship between the digital economy and agricultural trade also has its own characteristics, but there are few research studies in this area. At present, only Liu and Gao (2022), based on the data of total imports and exports of different agricultural products from 2004 to 2018, have established a vector auto-regressive model to empirically analyse the heterogeneous dynamic impact of the digital economy on the trade volume of agricultural products. In addition, Ma and Guo (2023) conducted an empirical test on the total effect, regional heterogeneity and threshold effect of the digital economy on agricultural export trade based on China’s provincial panel data from 2011 to 2020. Therefore, under the new circumstances of continuous integration of digital technology and agriculture, this study interprets the impact effect and mechanism of the digital economy on the binary margin of agricultural exports from the perspective of the digital economy, providing new research perspectives and approaches for promoting the growth of agricultural exports. Second, in terms of theoretical analysis, the above studies have not been fully analysed in terms of the specific mechanism of the impact of the digital economy on agricultural exports. Based on the positive and negative characteristics of agricultural trade, this study introduces two kinds of roles into the theoretical analysis framework to comprehensively determine the trade impact effect of the digital economy. Third, in terms of research design, this study empirically examines the impact of the digital economy on the binary margin of agricultural products, passing a series of robustness tests and investigating the mediating roles of trade cost and market competition effects, producing an empirical basis for China to leverage the digital economy to promote the binary margin of agricultural exports.

Preventing and tackling bullying effectively are important agenda for schools to safeguard all children’s well-being, engagement and sense of belongingness. Children perceived to be different from their peers tend to have a higher risk of being bullied at school, in particular, children with disabilities. It can be challenging for teachers to stop bullying that targets children with disabilities. This chapter considers bullying as a barrier to ensuring inclusive and quality education for everyone. It draws on findings from an ethnographic study concerning the status of inclusion of children identified as having learning difficulties in mainstream schools in China, by listening to what children and teachers have to say (Wang, 2016). The study found that the child participants were subject to forms of bullying. They found it useful to gain support from others when bullying happened, and they showed empathy towards peers’ well-being. The teacher participants reflected on the dilemmas and challenges of dealing with bullying and were keen to share experiences about what they found helpful in addressing the issue. The chapter discusses how insights about bullying learned from children and teachers can be used to inform the enactment of inclusive pedagogy. It is concluded that an inclusive pedagogical response that recognizes every child’s voice is necessary for tackling bullying and co-creating an inclusive environment.

Digital transformation is essential for commercial banks to maintain long-term competitiveness in the digital economy era. This study aims to investigate the relationship between inside debt and the bank's digital transformation.

This study set up a quasi-natural experiment based on implementing the executive compensation deferral system in the Chinese banking industry. Using the annual panel data of 180 commercial banks in China from 2007 to 2021, this study employed the difference-in-differences (DID) method to conduct an empirical analysis.

This study confirms a significant statistical relationship between inside debt and the bank's digital transformation, and managerial myopia is the transmission channel of inside debt affecting the bank's digital transformation. Furthermore, the development of Internet finance and the enhancement of bankers' confidence will improve the contributions of inside debt to the bank's digital transformation.

This study contributes to the literature on inside debt and the bank's digital transformation. It has specific policy value for the scientific design of the banking compensation mechanism and accelerating banks' digital transformation.

This study aims to explore key factors and specific ways for the upgrade to hybrid incubators in the context of China. A hybrid incubator means that a technology-based business incubators (TBIs) can implement various distinct value creation processes with the integration of the advantages of non-for-profit and for-profit TBIs at same time as Chinese government now requires government-sponsored non-for-profit TBIs to be profitable self-sustainability with less dependent on direct public subsidies, aiming to motivate these TBIs to provide higher quality services for their tenant new technology-based firms (NTBFs).

This study conducts a single in-depth case-study of Tuspark Incubator (located in Tsinghua Science Park [TSP]) with categorical analysis.

Three factors, i.e. incubation subdivision, intermediary platform and proactive approach, are found to be essential for a formerly government-sponsored TBI’s upgrading. Incubation subdivision enables Tuspark Incubator to create multiple incubation processes with incubator characteristic variables of both non-for-profit and for-profit incubators; with the establishment of intermediary platform, Tuspark Incubator provides specialized business support and high-quality networking from relevant specialized service organizations external to the incubator; more proactive approach with equity investment on incubating firms from Tuspark Incubator help to generate social welfare and financial profit at the same time.

For the incubators’ managers, incubation subdivision enables TBIs to operate for-profit and non-for-profit processes at the same time and provides different specific needs; more open intermediary service platforms can leverage the full potential of the actors in innovation system and help TBIs to save resource when upgrading to hybrid incubators; proactive approaches nurture learning climate and entrepreneurship environment to enhance the successful rate on NTBFs inside incubators and provide main profit source for incubators. For policy makers, using proactive approaches including creating a good milieu for incubation on technology-based start-ups and the design of public guidance funds is increasingly crucial.

This research is a pioneering study on the key factors and specific ways for the upgrade of government-sponsored non-for-profit TBIs in China to hybrid for-profit and non-for-profit incubators.

According to relevant research, non-uniform speed has a significant impact on the vehicle-track systems. Up to now, research work on it is still very limited. In this paper, the PEM is adopted to further transform it into a deterministic process to solve the vehicle’s problem of running at a non-uniform speed.

The multi-body vehicle model has 10 degrees of freedom and the track is regarded as a finite long beam supported by lumped sleepers and ballast blocks. They are connected via linear Hertz springs. The vertical track irregularity is a Gaussian stationary process in the space domain. It is transformed into a uniformly modulated nonstationary random process in the time domain with respect to the non-uniform vehicle speed. By solving the equation of motion of the coupled vehicle-track system with the pseudo-excitation method, the pseudo-response and consequently the power spectral density and the standard deviation of the structural response can be obtained.

Two kinds of vehicle braking programs are taken in the numerical example and some beneficial conclusions are drawn.

The pseudo-excitation method (PEM) was used to perform the random vibration analysis of a coupled non-uniform speed vehicle-track system. Transforming the track irregularity into a uniformly modulated nonstationary random process in time domain with respect to the non-uniform vehicle speed was undertaken. The pseudo-response of the coupled system is solved by applying the Newmark algorithm with constant space integral steps. The random vibration transfer mechanism of the coupled system is fully discussed.