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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.

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.

The purpose of this study was to develop a new folding method for modeling complicated folded fabric with surfaces of revolution.

Irregular wrinkles and mesh distortions easily appear in the fold modeling of a complex curved surface. Aimed at this key technical problem, the segmentation mapping folding method (SMFM) is proposed in this paper. First, high-precision flattened planes were obtained by using segmentation mapping techniques. Second, the segmented planes were transformed into a folded and continuous geometric model by using matrix transformations. Finally, initial stress was used to modify the geometric folding errors, which ensured agreement with the inflated flexible fabric’s geometry and the original design.

Compared with the traditional folding method, SMFM has the advantages of good finite-element mesh quality, large radial compression rate, regular folds, etc. The surface area error and the volume error of the inflated single torus established by SMFM were only 1.2 per cent, showing that SMFM has high modeling accuracy. The numerical results of an inflatable re-entry vehicle are presented to demonstrate the reliability, feasibility and applicability of SMFM. Moreover, the stress modification reduced the problems of stress concentration and mesh distortions, improving the accuracy and stability of the numerical calculations.

In this paper, for the first time, a folding method for modeling complicated folded fabric is proposed. This methodology can be used to model the multidimensional compression and regular folds of complex surfaces of revolution that cannot be flattened and to improve the accuracy and stability of the numerical calculations.

Swift guanxi and trust can influence consumers’ decision making in social commerce. What factors will influence the formation of swift guanxi and trust between buyers and sellers in social commerce has not been clearly investigated. The purpose of this paper is to identify antecedents and impacts of swift guanxi and trust in social commerce.

An online questionnaire was used to collect the data, and Partial Least Squares Structural Equation Modeling was employed for data analysis. Social support and presence are introduced as the antecedents for swift guanxi and trust, leading to the repurchase intention (RI) and social sharing intention of customers.

The results indicate that social support and presence can influence swift guanxi and trust. Social support and presence are positively associated with swift guanxi and trust which further lead to RI and social sharing intention.

The findings can be used to guide sellers in social commerce platforms to improve their services and make good use of platform features to improve customers’ perception of presence. To attract new customers and retain old customers, sellers should also build swift guanxi and trust through the recommendation and experience sharing of previous buyers on social media.

This study combines social support theory and presence theory to investigate the factors that influence customers’ purchase decision and social sharing intention in the context of social commerce in China. The integration of social support theory and presence theory explains both the social and technical factors that influence swift guanxi and trust in social commerce.

This study aimed to examine the impact of social influence and personal attitudes on users’ continuance intention. Based on social influence theory, this study developed a theoretical model to explore what factors can influence users’ social network sites continuance intention.

To validate the research model, the authors used an online survey instrument to gather data. Hypotheses were tested using partial least squares modeling.

Using a data set including 229 WeChat users in China, the authors found that the influence of subjective norms and group norms on continuance intention is insignificant. Moreover, social identity and personal attitudes were proved to be significant predictors of continuance intention. Specifically, gender played a moderating role in the relationship between social identity and continuance intention. In addition, gender moderated the effect of personal attitudes on continuance intention as well.

This study provided insights into how social influence affects users’ continuance intention. Moreover, this study concentrated on the different impact of social influence and personal attitudes on users’ continuance intention. Specifically, the authors explored gender differences in users’ continuance intention. The results extend the knowledge about the differences of males versus females in using social network sits.