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This study examines the effects of the online brand community's (OBC) humor climate on the value cocreation (VCC) behavior of consumers using the affective events theory. It also evaluates the serial mediating roles of positive emotions and brand engagement and the moderating effect of membership duration.

The authors collected data from 601 Chinese consumers of OBCs using an online questionnaire survey and applied structural equation modeling to analyze the data.

The authors found a positive relationship between OBC humor climate and VCC behavior, which was mediated by positive emotions and brand engagement. Additionally, there was a serial mediation effect of these two variables. The influence of the OBC humor climate on positive emotions was stronger for short-term members than long-term ones.

This research contributes toward OBC management and VCC marketing strategy for constructing brand equity.

This study is among the first to focus on the significance of the OBC humor climate, thus enriching the OBC literature and providing a new perspective on how to facilitate VCC behavior. It also broadens the application of the affective events theory in marketing.

Few extant studies have focused on digital rituals and investigated the relationship between them and customer citizenship behavior in the context of online brand communities (OBCs). This study aims to examine the sequential mediation mechanism of emotional energy and spiritual brand identification under interaction ritual theory and identifies membership prototypicality as the moderator.

An online investigation of 515 OBC users was conducted to gather data, and structural equation modeling was applied to test the hypotheses.

The empirical results revealed that OBC rituals were positively related to customer citizenship behavior. Emotional energy and spiritual brand identification could play mediating roles in the relationship between OBC rituals and customer citizenship behavior. Furthermore, there existed a sequential mediation mechanism with emotional energy as the first mediator and spiritual brand identification as the second. The effect of OBC rituals on emotional energy was more significant for peripheral members than prototypical members.

Managers of OBCs should conduct various ritualistic strategies to stimulate users to perform customer citizenship behaviors. Discrete ritualized activities should be intended for members of different prototypicalities.

This study provides a profound insight on how OBC rituals foster customer citizenship behavior and is among the first to explore such a relationship. It also investigates the sequential mediation mechanism, thus broadening the research on the influencing processes of OBC rituals on customer citizenship behavior.

The modified Reynolds equation for non-Newtonian lubricant is derived using the viscous adsorption theory for thin-film elastohydrodynamic lubrication (TFEHL) of circular contacts. The proposed model can reasonably calculate the phenomenon in the thin-film lubrication (TFL) unexplained by the conventional EHL model. The differences between classical EHL and TFEHL with the non-Newtonian lubricants are discussed.

The power-law lubricating film between the elastic surfaces is modeled in the form of three layers: two adsorption layers on each surface and one middle layer. The modified Reynolds equation with power-law fluid is derived for TFEHL of circular contacts using the viscous adsorption theory. The finite difference method and the Gauss–Seidel iteration method are used to solve the modified Reynolds equation, elasticity deformation, lubricant rheology equations and load balance equations simultaneously.

The simulation results reveal that the present model can reasonably calculate the pressure distribution, the film thickness, the velocity distribution and the average viscosity in TFL with non-Newtonian lubricants. The thickness and viscosity of the adsorption layer and the flow index significantly influence the lubrication characteristics of the contact conjunction.

The present model can reasonably predict the average viscosity, the turning point and the derivation (log film thickness vs log speed) phenomena in the TFEHL under constant load conditions.

Social network group decision-making (SNGDM) has rapidly developed because of the impact of social relationships on decision-making behavior. However, not only do social relationships affect decision-making behavior, but decision-making behavior also affects social relationships. Such complicated interactions are rarely considered in current research. To bridge this gap, this study proposes an SNGDM model that considers the interaction between social trust relationships and opinion evolution.

First, the trust propagation and aggregation operators are improved to obtain a complete social trust relationship among decision-makers (DMs). Second, the evolution of preference information under the influence of trust relationships is measured, and the development of trust relationships during consensus interactions is predicted. Finally, the iteration of consensus interactions is simulated using an opinion dynamics model. A case study is used to verify the feasibility of the proposed model.

The proposed model can predict consensus achievement based on a group’s initial trust relationship and preference information and effectively captures the dynamic characteristics of opinion evolution in social networks.

This study proposes an SNGDM model that considers the interaction of trust and opinion. The proposed model improves trust propagation and aggregation operators, determines improved preference information based on the existing trust relationships and predicts the evolution of trust relationships in the consensus process. The dynamic interaction between the two accelerates DMs to reach a consensus.

The purpose of this paper is to examine the indigenous Chinese concept of suzhi (素质) with the aim of furthering the development of Chinese human resource management (HRM) research and practice.

An extensive review of the literature on suzhi, published in the West, as well as in China, is the basis for proffering an organizational-level conceptualization of suzhi in the Chinese context.

Instead of understanding it as a free-floating signifier, we argue that suzhi can be considered as a criterion-based framework for HRM research and practice. Suzhi research is classified into two major sources – indigenous Chinese and indigenized Western constructs. We further make a distinction between intrinsic and extrinsic suzhi, and analyze a popular set of suzhi criteria, considering de (morality) and cai (talent), while focusing on de in HRM selection (德才兼备, 以德为先). As multilevel and multidimensional framework, suzhi criteria may form different gestalts in different organizations and industries.

From a social cultural and historical perspective, HRM research that incorporates a combination of indigenous and indigenized suzhi characteristics may receive better acceptance by individuals, organizations and the society in the Chinese context. Accordingly, the reconstruction of suzhi into manageable and measurable dimensions can be undertaken for more effective HRM practice in the Chinese context.

The HRM literature is advanced by linking the indigenous suzhi discourse to Chinese indigenous HRM research and practice.

Collaborative processes are relatively complex and are therefore difficult to handle. Representing the joint processes and capturing the interactions among stakeholders in a structured way are critical to improve the collaboration productivity. This paper aims to present a generic collaborative process model that improves on current approaches by explicitly representing the perspectives of stakeholders and their evolution traversing a work process.

This approach provides a mechanism to identify the interdependencies among tasks and stakeholders, and realizes collaboration through process management. A web‐based information system using the model to support collaborative process management is also described.

The research work provides collaboration management systems with the ability to analyze and control the processes through sharing perspectives.

The models and methods described in this paper are an important part of a pervasive, resilient and predictable means for business process management over the internet.

The purpose of this paper is to present a numerical analysis of the nonlinear dynamic response of a gear‐bearing system subject to nonlinear suspension effects, micropolar fluid, journal bearing, nonlinear oil‐film force and nonlinear gear mesh force. The results presented in this study provide some useful insights into the design and development of the system for rotating machinery that operates in highly rotational speed and highly nonlinear regimes.

The non‐dimensional equation of the gear‐bearing system proposed in this study is solved using the Runge‐Kutta method. The non‐periodic behavior of this system is characterized using phase diagrams, power spectra, Poincaré maps, bifurcation diagrams, Lyapunov exponents and the fractal dimension of the system.

The numerical results reveal that the system exhibits a diverse range of periodic, sub‐harmonic, quasi‐periodic and chaotic behaviors. The micropolar fluid is a useful lubricating fluid to suppress nonlinear dynamic responses and improve the dynamic regularity of the systems.

The unbalance coefficient, damping coefficient, other control parameters and some experiments are also important to identify dynamic behaviors of those systems and they may be regarded as research directions in the future.

Because of financial constraints, some important experiments are outstanding to identify dynamic behaviors of these systems and await research in the future.

This study has presented a numerical analysis of the nonlinear dynamic response of a gear‐bearing system with nonlinear suspension effects, micropolar fluid, journal bearing, nonlinear oil‐film force and nonlinear gear mesh force.

In the academic field of business management, several potential theories were established during the last decades to explain companies' decisions, organizational behavior, consumer patterns, and internationalization, among others. As a result, businesses and scholars were able to analyze and decide based on theoretical approaches to explain the current conditions of the market. Secondary research was conducted to collect more than 36 management theories. This chapter aims to develop the most famous theories related to business applied in the international field. The novelty of this chapter relies on the compilation of recognized previous research studies from the academic literature and evidence in international business.

The purpose of this paper is to present a committee machine (CM) with two‐layer expert nets to overcome the lack of approximating ability of CM with single‐layer expert nets.

A frequently used structure of CM, with a fuzzy c‐means clustering algorithm as splitting and combining unit and some single‐layer linear neural nets as expert modules, was applied to short‐term climate prediction. Considering the complexity of the climate conditions, use was made of two‐layer back propagation (BP) neural nets instead of single‐layer linear nets to test the effect of the model. Experiments were performed on both synthetic and realistic climatic data.

Prediction accuracy is raised when the BP nets were used and as the number of hidden neurons increased at some stages. It implies that improving the approximating ability of individual expert module of a CM is beneficial.

The optimal learning rate, the optimal cluster numbers and the maximal number of iteration were not well treated.

The paper is a useful alternative worth consideration for the complicated prediction problems.

A CM with two‐layer expert nets are presented. Comparisons are made between CMs with simple and complex expert nets.