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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.

National collaboration is an important topic for the development of digital humanities (DH). However, the collaboration patterns of DH have not been well studied in terms of development stages and collaboration characteristics. This paper aims to reveal the typical patterns of country-level collaboration in the global environment of DH based on research capacity, network features and influence indicators.

We systematically designed a pipeline procedure based on the methods of bibliometrics and altmetrics to analyze global DH-related publications from two popular databases. The process includes the division of development stages, the identification of typical characteristics, the analysis of collaboration networks and the correlation test for different influences across countries.

The findings show that the collaboration in DH has certain characteristics and evolutionary patterns – with 2007 as the turning point that presents a gradual alteration from the strong competition of nation giants and the dominance of domestic collaboration to diversified international cooperation within regional alliances and a clear positive effect on national influence (both academic and social levels) by international collaboration. Some relevant suggestions are also put forward.

The study demonstrates not only the evidence of distinct patterns of country-level collaboration for DH during its evolutionary period as well as collaboration types and structures but also the positive effect of international collaboration on the enhancement of both academic influence and social attention. Moreover, the proposed analytical procedure provides insightful ideas around DH development from both the bibliometric and altmetric views, which can be an extensible framework for other scholarly collaboration research.

In this digital age and risk society, this study aims to explore innovative strategies for E-retailers during supply chain disruptions to construct a more resilient supply chain system.

Various game theoretical models are constructed to analyze four supply chain scenarios. Meanwhile, sufficient numerical analysis was conducted to observe the impact of key parameters on supply chain strategies.

Multiple crucial factors exert a comprehensive influence on E-retailers’ decisions on sourcing and pricing, leading to the diversity and complexity of decision-making conditions. First, with the increased probability of disruption, the purchase quantities of the E-retailer from different suppliers are not in a linear changing pattern, and the total purchase quantity is allocated variably between different suppliers. Second, the variation in disruption severity (partial or complete) results in the shift of decisions between single-sourcing and dual-sourcing. Responsive pricing is conducive to increasing the purchase quantity and profits under partial disruption; its advantages are diminished when completely disrupted. Third, higher commission rates usually have a detrimental impact on profit, whereas responsive pricing may mitigate this impact.

Unlike the previous single perspective, this study innovatively explores strategies from the hybrid perspective of sourcing and pricing. By extracting two key factors (disruption probability and severity), it realizes the scientific characterization of supply chain disruptions. These achievements boost theoretical innovation. Concentrating on E-retailers, it avoids the generalization of conclusions and enhances the application value.

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.

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.

To address the various irregularities that occurred during the development of China’s electricity market, particularly the issue of collusive pricing between upstream and downstream firms.

This study constructs a tripartite evolutionary game model involving government regulators, grid operators and power producers to address electricity market pricing chaos. By analyzing the stable strategies within each subject’s evolutionary game, adjustments to the relevant parameters are made to achieve a stable state of strategy selection.

The findings of this study indicate the following: (1) Enhancing the government’s rewards and punishments, increasing speculation and rent-seeking costs for grid operators and modifying tariff sales revenue can promote the integrity of grid operators. (2) Establishing reasonable incentives and penalties can effectively mitigate rent-seeking behaviors resulting from collusive pricing in the power industry. (3) Strengthening the accountability of higher authorities to government regulators and adjusting incentives for grid operators to comply and generators to refrain from rent-seeking behavior can increase the likelihood of rigorous inspections by government regulators.

This study elucidates the impact of factors such as the cost of speculation and sales revenue of grid operators, the cost of rent-seeking by power producers and the strength of rewards and punishments by government departments on the power sector. Adjusting these factors can significantly influence the stability of the three-party evolutionary game, providing valuable insights into the regulatory mechanisms of the power industry.

The crowdsourcing software development platforms organize geographically distributed developers to complete various developing tasks, bringing convenience and efficiency to users. However, with the increasing number of both developers and tasks, it becomes more and more challenging to match tasks and suitable developers, especially for imbalanced data. The purpose of this paper is to propose an accurate and diverse recommendation model for crowdsourcing tasks.

A revised circle loss function is applied to achieve a certain adaptive ability, which is critical for imbalanced data, it guarantees diversity by maximizing the target label score and leveraging mathematical approximation to automatically balance the weights. Besides, the authors leverage the capsule network to obtain the semantic feature of tasks’ descriptions, modify the dynamic routing mechanism to better learn users’ preferences and improve the recommendation accuracy.

The comprehensive experiments conducted on real crowdsourcing platform data demonstrate that the proposed Crowd-CapsNet model can achieve high recommendation accuracy with a certain diversity. It improves around 1% accuracy with only 37% training time of the LSFA approach.

This paper proposes Crowd-CapsNet, an adaptive crowdsourcing task recommendation model. A relatively general feature pre-processing method describes crowd-sourcing tasks and the modified capsule network further obtains the semantic features to improve the recommendation accuracy and diversity.

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.