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This study aims to examine how the knowledge breadth and depth of a patent affect its likelihood of being pledged. It also seeks to explore whether these relationships change diversely in different technological environments.

A complementary log-log model with random effects was conducted to test the hypotheses using a unique data set consisting of 348,927 invention patents granted by the China National Intellectual Property Administration from 1985 to 2015 belonging to 74,996 firms.

The findings reveal that both knowledge breadth and depth of a patent positively affect its likelihood of being pledged. Furthermore, the knowledge breadth and depth entail different degrees of superiority in different technological environments.

This study focuses on the effect of an individual patent’s knowledge base on its likelihood of being selected as collateral. It does not consider the influence of the overall knowledge characteristics of the selected patent portfolio.

Managers need to pay attention to patents’ knowledge characteristics and the changes in technological environments to select the most suitable patents as collateral and thus improve the success rate of pledge financing.

This study explores the impact of multidimensional characteristics of knowledge base on patent pledge financing within a systematic theoretical framework and incorporates technological environments into this framework.

This study aims to analyse the relationship between a patent’s network position in a knowledge search network and the likelihood and speed of patent transactions. Additionally, it explores whether patent scope moderates these relationships.

In this empirical study, the authors collected a sample of patents in the artificial intelligence industry over the period of 1985–2018. Then, the authors examined the direct roles of degree centrality, betweenness centrality and closeness centrality on the likelihood and speed of patent transactions and the moderating role of patent scope in the knowledge search network using the logit and accelerated failure time models.

The findings reveal that degree centrality positively affects both the likelihood and speed of patent transactions, while betweenness centrality enhances the likelihood, and closeness centrality significantly boosts both. However, regarding the speed of patent transactions, closeness centrality is the most impactful, followed by degree centrality, with no significant influence of betweenness centrality. Additionally, the patent scope moderates how betweenness centrality affects the likelihood of transactions.

This study has limitations owing to its exclusive use of data from the Chinese Intellectual Property Office, lack of visibility of the confidential terms of most patent transactions, omission of transaction directionality and focus on a single industry, potentially restricting the breadth and applicability of the findings. In the future, expanding the data set and industries and combining qualitative research methods may be considered to further explore the content of this study.

This study has practical implications for developing a better understanding of how network structure in the knowledge search network affects the likelihood and speed of patent transactions as well as the identification of high-value patents. These findings suggest future directions for patent holders and policymakers to manage and optimise patent portfolios.

This study expands the application boundaries of social network theory and the knowledge-based view by conducting an in-depth analysis of how the position characteristics of patents within the knowledge search network influence their potential and speed of transactions in the technology market. Moreover, it provides a theoretical reference for evaluating patent value and identifying high-quality patents by quantifying network positions. Furthermore, the authors construct three centrality measures and explore the development of patent transactions, particularly within the context of the developing country.

This study aims to complement existing studies by investigating the impact of different corporate social responsibility (CSR) information disclosed by peer listed stars (i.e. governance information [GI] and output information [OI]) on focal firms’ responsive CSR (RCSR) and strategic CSR (SCSR) practices. The authors also investigate the influence of different boundary conditions (i.e. founders’ social status [SS] and industry pollution intensity).

Based on the listed stars of 16 industries and their 4,096 private peers in China, the authors use the least squares method and logistic regression models to analyze the data set.

The results indicate that the GI of peer listed stars can only positively affect firms’ RCSR behavior. The OI of peer listed stars has a positive effect on firms’ SCSR behavior while negatively affecting firms’ RCSR behavior. The SS of focal firms’ founders and their interaction with the industry’s pollution level strengthen the abovementioned positive relationships while weakening the negative ones.

This study provides insights into the role of listed stars in influencing peer firms’ CSR activities, offering important practical implications for both policymakers and managers.

This study extends the recent discussion on peer effects of CSR by elucidating the peer star effect on CSR and confirms that firms may adopt heterogeneous CSR practices to achieve sustainable growth by investigating peer firms’ different responses to their listed stars’ different CSR information. Moreover, by introducing the SS of founders and the pollution intensity of the industry as boundary conditions, this study enriches the research context on CSR activities.

This study aims to deliver a new perspective on how the interaction of independent and cooperative innovation affects firm digitization. Based on resource constraint theory, this study argues that the aforementioned interaction negatively affects firm digitization. The moderating role of managerial discretion is also discussed in light of the principles of the awareness-motivation-capability (AMC) framework.

The proposed hypotheses are empirically tested using a negative binomial modeling approach. The data used are from A-share listed companies in China’s Shanghai and Shenzhen stock markets from 2006 to 2020.

This study suggests that the interaction of independent innovation and cooperative innovation negatively impacts digitization. In addition, this study argues that environmental discretion and organizational discretion weaken the negative impact of the mentioned interaction on digitization. However, additional discretion in the Chinese context has no effect on above relationships.

This study explores the impact of the interaction of independent and cooperative innovation on digitization and incorporates managerial discretion into this framework based on the AMC framework.

Consumer co-creation is a relational process through which consumers’ experiences, resources and knowledge are exchanged. This study aims to investigate the indirect effects of social capital on consumer co-creation behaviors, especially citizenship behaviors, through psychological ownership.

A survey was designed to measure social network, trust and shared vision, psychological ownership and citizenship behaviors; it was completed by 527 users of the Ctrip. Using data from the survey, a PLS model was constructed to depict the relationships between the key variables.

The results showed psychological ownership mediated the relationship between social capital and citizenship behaviors. Specifically, the chain-mediating effects of social capital dimensions (i.e. social network, shared vision and trust) on citizenship behaviors through psychological ownership were validated.

The rise of social media as a platform for consumer co-creation calls for a fundamental rethinking of traditional approaches to collaboration between companies and consumers. This study offers several suggestions for tourism companies to better engage with consumers on social media platforms.

This study extends current research by introducing social capital theory as a theoretical foundation for exploring tourism social media and determining the mediating role of psychological ownership between social capital and citizenship behaviors.

The purpose of this paper is to study the dynamic behavior of complex-valued switched grey neural network models (SGNMs) with distributed delays when the system parameters and external input are grey numbers.

Firstly, by using the properties of grey matrix, M-matrix theory and Homeomorphic mapping, the existence and uniqueness of equilibrium point of the SGNMs were discussed. Secondly, by constructing a proper Lyapunov functional and using the average dwell time approach and inequality technique, the robust exponential stability of the SGNMs under restricted switching was studied. Finally, a numerical example is given to verify the effectiveness of the proposed results.

Sufficient conditions for the existence and uniqueness of equilibrium point of the SGNMs have been established; sufficient conditions for guaranteeing the robust stability of the SGNMs under restricted switching have been obtained.

(1) Different from asymptotic stability, the exponential stability of SGNMs which include grey parameters and distributed time delays will be investigated in this paper, and the exponential convergence rate of the SGNMs can also be obtained; (2) the activation functions, self-feedback coefficients and interconnected matrices are with different forms in different subnetworks; and (3) the results obtained by LMIs approach are complicated, while the proposed sufficient conditions are straightforward, which are conducive to practical applications.

Currently, consumers can easily access social media to share information and experiences. How a relationship between these consumers influences their decisions has not been clearly investigated. When consumers participate in information sharing activities, they usually communicate with each other and can perceive their social distance from others. Thus, the purpose of this paper is to explore the direct and indirect effects of perceived social distance on eWOM sharing intentions.

Specifically, a moderated mediation model was validated, in which the indirect effect of perceived social distance on eWOM sharing intentions through reciprocity expectations was moderated by trust.

Perceived social distance had a positive indirect effect on eWOM sharing intentions through reciprocity expectations, which was found to be negatively moderated by trust.

This study integrates the concept of perceived social distance into the eWOM research area. Moreover, this result adds to the s-commerce literature by specifying the conditions of the indirect effect of perceived social distance through reciprocity expectations on eWOM sharing intention.

Traditional Chinese Medicine (TCM) is a complete medical healthcare system that encompasses acupuncture, acupressure, moxibustion, herbal medicine, diet, tui na massage, and exercises (tai chi and qigong) among other traditional therapies. It uses herbs and natural resources to produce the traditional medicines and focuses on maintaining the balance between body and mind. As such, many aspects of TCM can be considered as green and sustainable. While there is market demand for TCM in some countries and among some communities, some others are still not aware of TCM. Moreover, there are fewer discussions in the academic platforms on TCM. This case highlights the scenario of TCM based on Malaysia’s perspective and discusses its challenges and prospects.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

Innovation quality is a critical component of enterprise innovation. Prior research primarily focuses on company-level and external policy-level factors that affect innovation quality, while ignoring social-level factors. Based on institutional isomorphism theory, this study examines how the innovation quality of three-dimensional institutional equivalence, which is an important and unique reference group for firms to follow the “law of imitation of close preference”, affects the likelihood of firms' innovation quality.

This study conducts firm random effects and industry/year fixed effects models using China's listed companies from 2002 to 2021.

This study finds that compared with the innovation quality of its other industry, community, or network peers, the innovation quality of three-dimensional institutional equivalence has a greater impact on firm innovation quality. Furthermore, technological intensity significantly increases the effect of three-dimensional institutional equivalence on focal company innovation quality, while financing constraints significantly attenuate this effect. Additionally, when there is no institutional equivalent, the innovation quality of network, industry, and community peers has significant positive effects on enterprise innovation quality. Heterogeneity analysis also indicates that, under the conditions of non-state-owned enterprises, a low regional legal environment, or low regional factor market development, three-dimensional institutional equivalence contributes significantly to firm innovation quality.

This study focuses on the effect of three-dimensional institutional equivalence on Chinese enterprises' innovation quality. Nonetheless, research samples from other countries are not considered in this study.

This study explores the impact of three-dimensional institutional equivalence on firm innovation quality within a systematic theoretical framework and incorporates firm attributes into this framework.