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This paper analyzes the effect of the Belt and Road Initiative (BRI) on firm green innovation upgrading using data on Chinese firms between 2009 and 2021.

The author adopts the staggered difference-in-difference (DID) method to estimate regressions, treating the proposal of the BRI in 2013 as a policy shock. Our analysis yields few findings.

The author yields few findings. First, the BRI can significantly promote Chinese firms green innovation upgrading. Specifically, the BRI can promote firm green innovation upgrading by 0.9%. Second, the BRI mainly promotes firms green innovation upgrading by promoting firms to increase green entrepreneurship, cooperative innovation and environmental investment. Finally, the BRI has a greater impact on the green innovation upgrading of firms in the digital industrialization industry rather than digital industry and firms with low pollution emissions rather than firms with high-pollution emissions. This research indicates that the BRI is not only an important platform for sustainable development and also an important opportunity for green entrepreneurship.

First, due to the low quality of data and the lack of detailed information on some firms' patents owned after 2018, fully applying data of all years for regression was not possible. Second, the author did not construct a theoretical model to explore the impact of the BRI on green innovation upgrading of firms from the perspective of outward foreign direct investment (OFDI), which is also the direction of future research. Finally, there are still some unexplored mechanisms of the BRI on firms green innovation upgrading, which should be further explored in the future.

First, from the micro perspective, the author measures the quality of firms' green patents, further measuring the firms' green innovation upgrading. Second, the author discusses the impact of the BRI on firm green innovation upgrading with the method of staggered DID, so that the policy effect of the BRI can be more accurately evaluated. Third, the author comprehensively analyzes the mechanism of cooperative innovation and green infrastructure investment, as well as analyzing the heterogeneity from the perspective of industry digital transformation and firm pollution emissions. Lastly, the author provides specific paths for firms to make high-quality investment from the green BRI construction.

In recent years, the demand for road traffic has continued to increase, but the casualties and economic losses caused by traffic accidents have also remained high. Therefore, the use of social service robots to manage, supervise and warn real-time traffic information has become an inevitable trend of traffic safety management.

In order to explore the inherent objective development law of road traffic accidents, in this paper, the factor analysis (FA) is used to explore the main influencing factors of traffic accidents, then the random forest algorithm is applied to build an FA–RF-based road traffic accident severity prediction model to predict two- and three-category accidents.

By comprehensively comparing the classification results of the two- and the three-category accident prediction, it also finds that due to the intersection between injuries and fatalities and the lack of necessarily external environmental information, the FA–RF model has a large degree of misjudgment for injuries and fatalities. Therefore, it is recommended to establish a real-time autonomous information communication mechanism between different kinds of social robots, which can improve the prediction of traffic accidents.

(1) A fusion model of FA–RF is considered to predict traffic accidents, which can be applied in traffic service robot. (2) It is recommended to establish a real-time autonomous information communication mechanism between different kinds of social robots, which can improve the prediction of traffic accidents.

The quad‐rotor is an under‐actuation, strong coupled nonlinear system with parameters uncertainty, unmodeled disturbance and drive capability boundedness. The purpose of the paper is to design a flight control system to regulate the aircraft track the desired trajectory and keep the attitude angles stable on account of these issues.

Considering the dynamics of a quad‐rotor, the closed‐loop flight control system is divided into two nested loops: the translational outer‐loop and the attitude inner‐loop. In the outer‐loop, the translational controller, which exports the desired attitude angles to the inner‐loop, is designed based on bounded control technique. In consideration of the influence of uncertain rotational inertia and external disturbance, the backstepping sliding mode approach with adaptive gains is used in the inner‐loop. The switching control strategy based on the sign functions of sliding surface is introduced into the design procedure with respect to the input saturation.

The validity of the proposed flight control system was verified through numerical simulation and prototype flight experiment in this paper. Furthermore, with relation to the flying, the motor speed is kept in the predetermined scope.

This article introduces a new flight control system designed for a quad‐rotor.

The purposes of this study are to demonstrate the conditional effect of functional fit and image fit on consumer brand attitude through the altruistic attributions and identify the criteria for choosing a perfect social cause for managers.

Based on the existing research, a conceptual model is proposed, explained the moderating effect of social cause affinity on the indirect influence of functional fit and image fit on consumer brand attitude via altruistic attributions; these relationships were assessed through a bootstrap procedure. The model was estimated with a sample of 240 subjects. Two newly created, printed corporate social responsibility (CSR) information served as the basic stimulus of this article.

The main conclusions are as follows: first, social cause affinity moderates the effect of functional fit and image fit on altruistic attributions, and the combination of image fit and social cause affinity both on high levels can more easily lead to the emergence of suspicion of company's altruistic motives, contrary to functional fit. Second, contingent on social cause affinity, CSR fit has an indirect relationship with consumer brand attitude mediated by altruistic attribution. More specifically, the indirect effect will be more positive for functional fit with higher levels of social cause affinity, but for image fit with low levels of affinity.

The experiment relied on fictitious corporate name. Most of the responders were students from Changchun. This may reduce the generalizability of the results.

Besides functional fit and image fit, social cause affinity should be treated as a key criterion to choose social cause.

This work analyses and compares the indirect effect of functional fit and image fit on consumer brand attitude through altruistic attributions. The findings give some enlightenment on solutions to contradictions in existing research.

Details a new type of screwing mechanical hand which has been developed. There are three distinguishing features on the structures and functions of the mechanical hand: it can perform both screwing and unscrewing automatically; it has no special driver for its finger grasp and release but adopts some specific mechanisms and structures for this process; and the preset screwing torque is used to control the release of the fingers. Describes the main parts and operating process of the hand; the structure and movements of the wrist and hand; and the principle behind the grasp and release mechanism.

The purpose of this paper is to discover an effective maize price for trading and policy-making reference by assessing the price transmission of the US spot and futures maize prices to Chinese counterparts.

The authors apply a systematic, quantitative method to analyze the integration between US and Chinese maize markets. Based on the residuals of the variables through error correction model, the directed acyclic graph (DAG) among six price variables is conducted. With consideration of the dependence on and direction of six price variables, the variance decomposition of each variable is calculated.

This paper shows that the vertical price transmission passes from wholesale price to farm-gate price. The horizontal price transmission ranges from spot price to futures price at the domestic market and from the American spot price to domestic spot price, from the American spot price to domestic futures price and from the American futures price to domestic futures price. The American maize spot and futures prices, and in particular the spot price, have greater effects on domestic maize prices contemporaneously. It also indicates that the American spot price is the leader price in the long run at both maize markets.

This paper contributes by using the DAG method in this paper. It also contributes by helping policy makers and market participants find the leading prices and offers insight into ways of gaining power of price setting in the maize market.

In the digital era, the competitiveness of an enterprise is highly dependent on the success of its digital transformation. The effectiveness of such transformation, in turn, relies heavily on the organization's strategic vision and resource fitness. Accordingly, the authors aim to explore the impact of strategic vision on digitalization (SVD) on the digital transformation of small- and medium-sized enterprises (SMEs), drawing on the perspective of resource orchestration theory.

Based on first-hand interview data from 347 Chinese SMEs, the research model was tested empirically by both Structural Equation Modeling and Fuzzy Set Qualitative Comparative Analysis (fsQCA).

The study results supported that the positive effect of SVD on digital transformation, and the mediating effect of resource orchestration (resource structuring, resource bundling and resource leveraging) accounts for the relationship between SVD and digital transformation. Further, the fsQCA showed that neither SVD nor resource orchestration alone constitutes a necessary condition for high digital transformation in SMEs, and that SVD and resource orchestration elements constitute three configuration paths that drive SMEs to achieve high-level digital transformation.

To the authors knowledge, this is the first study of its kind to theorize and empirically examine how SVD affects SMEs digital transformation. In addition, the authors have highlighted the importance of resource orchestration in forging a link between SVD and digital transformation. The research contributes to the resource orchestration theory and digitalization literature and provides guidelines on how SMEs can realize digital transformation.

According to relational contract theory, relational governance has potential to improve public-private partnership (PPP) infrastructure project sustainability. The main purpose of this research is to investigate the association between relational governance and the sustainability of PPP infrastructure projects. Further, this study examines the mediating effect of managerial innovation and the moderating role of public involvement.

Research data were collected from 158 valid questionnaires completed by Chinese PPP professionals. Structural equation modeling (SEM) was then employed to test five hypotheses.

Results indicate a positive correlation between relational governance and PPP infrastructure project sustainability. This linkage is regulated by public involvement. In addition, managerial innovation plays a mediating role between relational governance and the sustainability of PPP infrastructure projects.

This study verifies the relationship between relational governance and PPP infrastructure project sustainability, as well as intermediary and regulatory factors, providing a new approach to achieving sustainability in PPP infrastructure projects.

Customer knowledge from social media can become an important organizational asset. The purpose of this paper is to identify useful customer knowledge including knowledge for customer, knowledge about customers and knowledge from customers from social media data and facilitate social media-based customer knowledge management.

The authors conducted a case study to analyze people’s online discussion on Twitter regarding laptop brands and manufacturers. After collecting relevant tweets using Twitter search APIs, the authors applied statistical analysis, text mining and sentiment analysis techniques to analyze the social media data set and visualize relevant insights and patterns in order to identify customer knowledge.

The paper identifies useful insights and knowledge from customers and knowledge about customers from social media data. Furthermore, the paper shows how the authors can use knowledge from customers and knowledge about customers to help companies develop knowledge for customers.

This is an original social media analytics study that discusses how to transform large-scale social media data into useful customer knowledge including knowledge for customer, knowledge about customers and knowledge from customers.

Social shopping platforms have flourished by using multiple social shopping features, yet little is known about how the combination of these features affects purchase intention, particularly in terms of the product itself. The purpose of the paper is to draw on the concept of social shopping feature richness, adopting a formative approach on the survey used, and endeavors to reveal the concept's impact on consumers' buying intention from a product perspective.

Building on mental accounting and signaling theories, a theoretical model is proposed and empirically evaluated with 356 samples collected using a questionnaire survey.

The results suggest that social shopping feature richness promotes consumers' consumption by providing information signals to satisfy acquisition utility and transaction utility. Specifically, social shopping feature richness enhances perceived product quality, while decreasing negative perceptions regarding price. Moreover, perceived product quality and perceived price significantly influence buying intention through the mechanism of perceived value.

The authors' study highlights the role of the combination of functionally diverse social shopping features on product sales for social shopping platforms.