Search results

This study delves into the nuanced relationship between financial constraints, ownership structures (state-owned and foreign) and innovation engagement within China’s A-share market, aiming to uncover how these dynamics vary across different industries and regional contexts.

By retrieving data from various datasets in China (2010–2022), this study analyzed the effectiveness of each variable, employing various dimensions to reflect innovation engagement among Chinese listed companies. Meanwhile, for the measurement of financial constraints, this study tested all four typical ones and opted for the KZ Index, as it is the most suitable for China’s A-share market. Then, by fixing the industry and year effects, the study examined the main and moderating effects. At last, in order to address endogeneity issues and capture the dynamic nature of innovation activities, this study follow the suggestion of Khatib (2024) and employed the two-step system Generalized Method of Moments (GMM) estimation.

The results demonstrate that while the government has introduced many policies to promote innovation, state-owned ownership does not consistently enhance innovation engagement as expected, especially when firms are in financial dilemma. Particularly, in Hi-tech industries, foreign ownership demonstrates greater interest and confidence in the innovation capabilities of China’s A-share market. Findings also reveal significant regional heterogeneity in the moderating role of ownership structures. While state-owned and foreign ownerships have a buffering effect against financial constraints in the eastern and western regions, but this effect is notably different in the middle part, even though it is China’s political heartland.

The findings offer a different insight for policymakers and corporate strategists, suggesting that targeted financial and regulatory policies that leverage specific ownership structures can foster innovation in different ways, particularly in financially constrained environments. However, how to stimulate innovation vitality in the middle part of China still requires further research.

In order to improve the efficiency and reliability of simulation analysis for composite riveting structures in engineering products, a comparative study was conducted on different forms of riveting simulation methods.

Five different rivent simulation models were established using the finite element method, including rigid element CE, flexible element Rbe3 and beam element, and their results were future compared and analyzed.

Under the given technical parameters, the simulation method of Rbe3 (with holes) + beam can meet the analysis requirements of complex engineering products in terms of the rationality of rivet load distribution, calculation error and relatively efficient modeling.

This study proposes a simulation method for the riveting structure of carbon fiber composite materials for engineering applications. This method can satisfy the simulation analysis requirements of transportation vehicles in terms of modeling time, computational efficiency and accuracy. The research can provide technical support for the riveting process and mechanical analysis between carbon fiber composite components in transportation products.

In the brain imaging based on electrical impedance tomography, it is sometimes not able to attach 16 electrodes due to space restriction caused by craniotomy. As a result of this, the number of boundary measurements decreases, and spatial resolution of reconstructed conductivity distribution is reduced. The purpose of this study is to enhance reconstruction quality in cases of limited measurement.

A new data expansion method based on the shallow convolutional neural network is proposed. An eight-electrode model is built from which fewer boundary measurements can be obtained. To improve the imaging quality, shallow convolutional neural network is constructed which maps limited voltage data of the 8-electrode model to expanded voltage data of a quasi-16-electrode model. The predicted data is compared with the quasi-16-electrode data. Besides, image reconstruction based on L1 regularization method is conducted.

The results show that the predicted data generally coincides with the quasi-16-electrode data. It is found that images reconstructed with the data of eight-electrode model are the poorest. Nevertheless, imaging results when the limited data is expanded by the proposed method show large improvement, and there is a minor difference with the images recovered with the quasi-16-electrode data. Also, the impact of noise is studied, which shows that the proposed method is robust to noise.

To enhance reconstruction quality in the case of limited measurement, a new data expansion method based on the shallow convolutional neural network is proposed. Both simulation work and phantom experiments have demonstrated that high-quality images of cerebral hemorrhage and cerebral ischemia can be obtained when the limited measurement is expanded by the proposed method.

By adopting learning theory and a guanxi perspective, this study aims to investigate the effects of interpersonal guanxi (interpersonal networks or connections) and relationship learning on companies’ business performance when operating in a large emerging market.

Using a sample of 294 sales managers and salespeople in the Chinese hotel sector, the authors empirically test the authors' arguments through a structural equation modeling (SEM) approach.

The authors' findings indicate that strong interpersonal guanxi tends to generate more positive business performance. Furthermore, the authors find that relationship learning plays a mediating role in the association between interpersonal guanxi and hotel companies’ business performance in a Chinese context. Finally, the authors empirically explore the moderating effect of inter-firm dependence on the contribution of interpersonal guanxi to relationship learning. Findings demonstrate that this effect varies significantly based on inter-firm dependence, with interpersonal guanxi exhibiting a greater positive impact if such dependence is high.

This study enriches our understanding of interpersonal guanxi and of how companies can enhance the companies' business performance in an emerging market context.

This paper aims to investigate how digital orientation affects digital process innovation from the dual perspectives of knowledge and capability. It also stresses the mediating effects of digital knowledge creation and strategic flexibility on this relationship, as well as the moderating effect of strategic flexibility on the relationship between digital knowledge creation and digital process innovation.

This paper adopted knowledge- and capability-based views to develop the theoretical model. A total of 193 samples from China were collected to test the model and hypotheses by the partial least squares structural equation modeling method.

The results indicate that digital orientation promotes knowledge creation and strategic flexibility respectively, which in turn facilitates digital process innovation. Also, the effect of digital knowledge creation on digital process innovation is moderated by strategic flexibility.

This study adopts the dual perspectives of knowledge and capability to deepen the relationship between digital orientation and digital process innovation by introducing digital knowledge creation and strategic flexibility as the crucial links, which responds to the call for attaching importance to digital process innovation.

Construction safety resilience is gradually gaining attention in the field of engineering construction as a new management concept and way to improve safety performance. However, how to cope with the dilemma of the unclear relationship of construction safety resilience elements at the practice level and promote the harmonization of construction safety goals and resilience enhancement paths has become an urgent challenge for safe construction.

This study analyzes the components of construction safety resilience elements. A relationship network model of construction safety resilience elements is developed by using the social network analysis method. The location and influence of each element in the network and the interrelationships among the elements are explored in depth.

The findings reveal a robust interconnection among the elements of safety resilience in the construction industry. Key components such as safety behavior, risk prevention and control mechanisms, disaster prevention and mitigation technologies as well as information technology, are positioned at the core of the network. Notably, safety behavior exerts the most significant influence over the other elements, serving as the linchpin of safety management in the construction industry. Moreover, the interplay among safety resilience elements in the construction sector can alter the structure of the relationship network.

This study adopts the social network approach to solve the problem that it is difficult to quantitatively analyze the elements of construction safety resilience and their interrelationships and to clarify the interactions among the core elements, which can help to further assist the construction project manager to continuously optimize safety resilience and improve construction safety.

Considering the importance of employees' voice behavior (VB) and psychological capital (PC) amidst the coronavirus disease 2019 (COVID-19), this study highlights the role of authentic leadership (AL) in building a psychologically strong workforce that can provide meaningful suggestions for the improvement of organization.

The study employed a questionnaire survey to collect the data and recruited 261 participants from the telecom sector Sindh, Pakistan. The data analysis was done using partial least squares structural equation modeling (PLS-SEM).

The findings of the study supported the hypotheses suggesting that AL can directly influence employees' VB and indirectly via PC.

The study was conducted during the COVID-19 in the telecom sector of Sindh, Pakistan. This study contributes by providing useful insights into that AL is an important form of leadership that encourages employees' voluntary behavior and psychological strength during the COVID-19 pandemic.

This paper aims to evaluate the effect of commitment misperception on channel conflict. It highlights the importance of trust and transaction-specific investments for business marketing strategies.

This paper develops a concept framework to understand how the direction (overestimated vs underestimated) and extent of commitment misperception influence channel conflict. The model is tested using dyadic data from 212 distributors and manufacturers across several industries in China.

The results show that the direction of commitment misperception affects trust, transaction-specific investments and channel conflict. Overestimated commitment induces positive illusion and enhances trust and transaction-specific investments and reduces channel conflict, whereas underestimated commitment induces negative illusion and reduces trust and transaction-specific investments and enhances channel conflict. Trust and transaction-specific investments mediate the impact of the direction of commitment misperception on channel conflict. The extent of commitment misperception plays the moderating influence on the direction of commitment misperception.

This study reveals the mechanisms and boundary conditions by exploring the mediating influence of trust and transaction-specific investments and the moderating effects of the extent of commitment misperception.

This study examines the effects of risk reduction, seller reputation, eWOM and warranties on consumer confidence and online impulse buying intentions through the lens of the stimulus-organism-response (SOR) model. It also explores the role of installment options in online impulse buying.

We performed a between-subjects experiment (installment vs. no-installment option). Data were collected from 199 consumers and analyzed using SmartPLS 3.3.9.

The results show that risk reduction, eWOM and warranty positively affect consumer confidence (CC) in online shopping and that CC positively predicts online impulse buying intentions. It was also found that the effect of CC on online impulse buying intentions was stronger when consumers were offered an installment option than a no-installment option.

Findings suggest that online sellers should invest more resources in building consumer confidence, which affects online impulse buying intentions. Moreover, online sellers should offer installment options to consumers, thereby reaping stronger effects of consumer confidence on online impulse buying intentions.

Employing the experimental approach, this study makes a novel attempt to examine the role of the installment option in fostering online impulse buying intentions among Pakistani consumers. Likewise, this is one of the early studies to explore the effects of risk reduction, seller reputation, eWOM and warranties on CC among Pakistani consumers using the SOR model.

To explore how the blockchain affects the pricing and financing decisions in a low-carbon platform supply chain.

Considering the dual roles of the e-commerce platform as a seller and an initiator, a typical game-theoretical method is applied to analyze the behavior of supply chain decision-makers and the impact of key variables on equilibriums.

When loan interest rates are symmetric, whether blockchain is used or not, the e-commerce platform financing mode will always produce higher wholesale price and unit carbon emission reduction, while the retail price is the opposite. Higher unit additional income brought by the blockchain can bring higher economic and environmental performances, and the e-commerce platform financing mode is superior to bank financing mode. The application of blockchain may cause the manufacturer to change his/her financing choice. For bank financing, with the increase of loan interest rates, the advantages brought by blockchain will gradually disappear, but this situation will not occur under e-commerce platform financing.

Blockchain is known for its information transparency properties and its ability to enhance user trust. However, the impacts of applying blockchain in a low-carbon platform supply chain with different financing options are not clear. The authors examine the manufacturer's strategic choices for platform financing and bank financing, whether to adopt blockchain, and the impact of these decisions on carbon emissions reduction, consumer surplus and social welfare. The research conclusion can provide reference for the operation and financing decisions of platform supply chain under the carbon reduction target in the digital economy era.