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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 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.

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.

Electronic word-of-mouth (eWOM) has become one of the most influential information sources for consumers' purchase decision-making. Based on construal-level theory and from the perspective of cognitive effort, this study investigated the effects of eWOM social media types and conflicting eWOM on consumers' purchase intentions and validated the mediation role of social psychological distance, perceived value, and perceived cognitive effort.

Two scenario-based experiments were conducted to validate the research model. Specifically, a 2 (eWOM social media type: strong-tie vs weak-tie) × 2 (conflicting eWOM: with vs without) between-subjects design was used. ANOVA, multiple regression analysis with PROCESS, and partial least squares (PLS) were employed to test the hypotheses.

The results showed that eWOM social media types had significant effects on both social psychological distance and perceived value. The significant chain mediating effects of social psychological distance and perceived value between eWOM social media types and consumers' purchase intentions were found. In addition, conflicting eWOM had significant effects on both perceived value and perceived cognitive effort. Indirect effects of conflicting eWOM on purchase intention through perceived cognitive effort were discovered.

These results contribute to the eWOM literature by investigating the influences of eWOM social media types and conflicting eWOM on consumers' purchase intentions. They also contribute to construal-level theory by extending its applicability to the field of eWOM.

The application of artificial intelligence (AI) in the customer market has completely changed customer behaviors. This study aims to investigate the customers' co-creation experiences with AI in the digital age.

An online survey was used to collect data from 699 customers who had used AI-enabled banking services. Hypotheses were validated using partial least squares modeling.

The findings indicate that the customer response capabilities (e.g. perceived response expertise and perceived response speed) serve as the intermediate processes between the AI service quality and the overall co-creation experience with AI. Moreover, AI function-customer ability fit negatively moderates the direct relationship between the AI service quality and the overall co-creation experience with AI.

This study improves the current understanding of co-creation by investigating the human–machine co-creation (e.g. customer–AI co-creation) instead of human–human co-creation.

The purpose of this paper is to investigate the impact of corporate social responsibility (CSR) on the performance of service innovation (PSI), and the mediating effect of knowledge acquisition.

Drawing on social exchange and knowledge management theories, this paper establishes a relevant conceptual model and adopts a hierarchical regression analysis to examine the model with a data set of 298 firms from China.

CSR positively affects the PSI; however, the effects vary when firms take responsibility for different stakeholders. CSR for the same group of stakeholders influences differently the short-term financial and long-term non-financial PSI, whereas knowledge acquisition mediates the impact of employee and customer CSR on PSI, but not the impact of community CSR on PSI.

Managers could improve the PSI of the firm by strategically assuming CSR and by managing corporate knowledge acquisition activities.

This study contributes to the service innovation literature by identifying the influence of particular types of CSR on PSI, and by highlighting the influencing mechanism of knowledge acquisition. It extends scholarly understanding of the antecedents of PSI as well as the business returns to CSR.

Social recommender systems have recently gained increasing popularity. The purpose of this paper is to investigate the influences of informational factors on purchase intention in social recommender systems.

Specifically, this study validated the mediating effect of trust in recommendations and the perceived value between informational factors and consumers’ purchase intention.

The results confirm that recommendation persuasiveness was a strong predictor of trust in recommendations and perceived value. Recommendation completeness was positively related to trust in recommendations and perceived value as well. Trust in recommendations and perceived value was found to be strong drivers of purchase intention.

The author identifies two sets of informational factors, i.e. recommendation persuasiveness and recommendation completeness, which are relevant to consumer attitudes. The current study proved that informational factors on consumers’ purchase intention are fully mediated through trust in recommendations and perceived value.