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There is considerable research examining the consequences and contingency factors of customer participation in the service encounter. In comparison, there is disproportionately less research examining the antecedents of customer participation. This paper aims to propose and test an appraisal-emotive framework of the effects of front-line employees’ in-role and extra-role behaviours on customer participation.

A survey on 583 customers of retail banks in China has been conducted to test the framework. Structural equation modelling and dominance analysis have been used for hypotheses testing.

Employees’ extra-role behaviour (i.e. organisational citizenship behaviour or OCB) has a stronger effect than their in-role behaviour (i.e. role-prescribed behaviour) in inducing customer participation. These effects are mediated by customer emotions. Specifically, the effect of employees’ in-role behaviour on customer participation was mediated by customers’ positive and negative emotions, whereas the effect of employees’ OCB was mediated by customers’ positive emotions but not by their negative emotions.

The findings reveal that strategic management of employee behaviours can influence customer participation. While organisations often provide training to enhance employees’ in-role behaviour to deliver service performance, they should also recognise and encourage employees’ OCB as a means of increasing customer participation. In particular, employees who display positive emotions tend to evoke positive emotions in customers, which increase customer participation in the service encounter.

To the authors’ knowledge, this is one of the few studies in marketing to examine the differential effects of employees’ in-role and extra-role behaviours on customer participation. Importantly, the findings show that employees’ OCB is not only more effective than employees’ in-role behaviour in influencing customer participation but also these two behaviours have varying effects on customer emotions. These findings are new and contribute to the literatures on customer participation, value co-creation and human resource management.

Heavy fog results in low visibility, which increases the probability and severity of traffic crashes, and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers. This paper aims at exploring the effects of dynamic message sign (DMS) of fog warning system on driver performance.

First, a testing platform was established based on driving simulator and driver performance data under DMS were collected. The experiment route was consisted of three different zones (i.e. warning zone, transition zone and heavy fog zone), and mean speed, mean acceleration, mean jerk in the whole zone, ending speed in the warning zone and transition zone, maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected. Next, the one-way analysis of variance was applied to test the significant difference between the metrics. Besides, drivers’ subjective perception was also considered.

The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone. Besides, when drivers enter a heavy fog zone, DMS can reduce the tension of drivers and make drivers operate more smoothly.

This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform. The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.

Bismaleimide (BMI) is a kind of thermosetting resin and its application is usually limited by low toughness. In this paper, two kinds of reinforcement intercalator amino-terminated polyoxypropylene (POP) and octadecyl trimethyl ammonium chloride (OTAC) were designed and synthesized to toughen BMI resin and the toughening effect was compared and analyzed. The purpose of this paper is to toughen BMI resin and analyze the toughening effect of two reinforcements intercalator amino-terminated polyoxypropylene (POP) and octadecyl trimethyl ammonium chloride (OTAC).

Sodium-based montmorillonite (Na-MMT) was modified by POP and OTAC, and the ion-exchange reaction obtained organic montmorillonite (POP-MMT and OTAC-MMT). The polymer matrix (MBAE) was synthesized, in which 4,4’-diamino diphenyl methane BMI was used as the monomer and 3,3’-diallyl bisphenol A and bisphenol A diallyl ether were used as active diluents. And then, POP-MMT/MBAE and OTAC-MMT/MBAE composites were prepared using MBAE as matrix and POP-MMT or OTAC-MMT as reinforcement. The Fourier-transform infrared, X-ray diffraction and scanning electron microscope (SEM) of the filler and microstructure and mechanical properties of the composite were characterized to the better reinforcement.

POP-MMT and OTAC-MMT enhanced BMI-cured products’ toughness by generating microcracks in the polymer to absorb more fracture energy. Meanwhile, POP-MMT and OTAC-MMT were the main stress components and the enhancement of the interface interaction was beneficial to transfer the external force from the matrix to the reinforcement and improved the mechanical properties of the composite. Furthermore, with the intercalation rate increasing, the compatibility of the two phases was increased and the performance of MBAE was also elevated.

BMI is generally used as aerospace structural materials, functional materials, impregnating paint and other fields. However, high crosslinking density leads to moulding material’s brittleness and limits a wider range of applications. Therefore, it has become an urgent priority to explore and improve the mechanical properties of BMI resin.

POP and OTAC have successfully intercalated Na-MMT layers to get POP-MMT and OTAC-MMT, and the interplanar crystal spacing and the intercalation rate were calculated, respectively. The results were corresponding with the SEM images of POP-MMT and OTAC-MMT. After that, the morphology of composites illustrated the compatibility was related to the intercalation rate. According to the mechanism of modified MMT toughening epoxy resin, when they were dispersed uniformly in the matrix, the composite’s mechanical properties had been significantly improved. Additionally, OTAC-MMT with a higher intercalation rate had better compatibility and interfacial force with the matrix, so that the mechanical properties of OTAC-MMT/MBAE were the best.

In the era of mobile internet, the social Q&A community has built a large-scale and complex knowledge label network through its internal knowledge units, and the scale and structure of the network have changed over time. By analysing the structural characteristics and evolution rules of knowledge label networks, the main purpose of this study is to understand the internal mechanisms of the replacement of old and new knowledge and the expansion of knowledge element boundaries, so as to explore the realization path of knowledge management in the new era from the perspective of complex networks.

This paper uses distributed crawlers to capture 419,349 samples from the Zhihu platform. Each sample contains 33 characteristic dimensions, and the natural year is used as the sliding window to divide the whole. In this study, the global knowledge label network and 11 local knowledge label networks are first constructed. Then, the degree distribution analysis and central node exploration of the knowledge label network are carried out using the complex network method. Finally, the average shortest path and average clustering coefficient of the network are analysed by the time series method, and the ARIMA model is used to predict the evolution of the correlation coefficient.

The research results show that the dissimilation degree of the degree distribution of the knowledge label network has gradually decreased from 2011 to 2021, and the attention of users in the knowledge community has shown a trend of distraction and diversification over time. With the expansion of the scale of the knowledge label network and the transformation to an information network, the network sparsity is becoming more and more obvious, and the knowledge granularity of the Q&A community is being refined and diversified. The prediction of the correlation coefficient of the knowledge label network by the ARIMA model shows that the connection between the labels is lacking diversity and the opinion strengthening phenomenon tends to strengthen, which is more likely to form the “echo chamber effect”, resulting in mutual isolation and even opposition between different circles. The Q&A community is about to enter a mature stage, and the corresponding status of each label has been finalized. The future development trend of label networks will be reflected in the substitution between labels, and the specific structure will not change significantly.

The Q&A community model is the trend in Web 2.0 community development. This study proves the effectiveness of complex networks and time series prediction methods in knowledge label network mining in the Q&A community.

Integrality of surface mesh is requisite for computational engineering. Nonwatertight meshes with holes can bring inconvenience to applications. Unlike simple modeling or visualization, the downstream industrial application scenarios put forward higher requirements for hole-filling, although many related algorithms have been developed. This study aims at the hole-filling issue in industrial application scenarios.

This algorithm overcomes some inherent weakness of general methods and generates a high-level resulting mesh. Initially, the primitive hole boundary is filled with a more appropriate triangulation which introduces fewer geometric errors. And in order for better performances on shape approximation of the background mesh, the algorithm also refines the initial triangulation with topology optimization. When obtaining the background mesh defining the geometry and size field, spheres on it are packed to determine the vertex configuration and then the resulting high-level mesh is generated.

Through emphasizing geometry recovery and mesh quality, the proposed algorithm works well in hole-filling in industrial application scenarios. Many experimental results demonstrate the reliability and the performance of the algorithm. And the processed meshes are capable of being used for industrial simulation computations directly.

This paper makes input meshes more adaptable for solving programs through local modifications on meshes and perfects the preprocessing technology of finite element analysis (FEA).

Controversial information systems (IS) represent a unique context in which certain members of a user's social circle may endorse the use of a system while others object to it. The purpose of this paper is to explore the simultaneous and often conflicting roles of such positive and negative social influences through social learning and ambivalence theories in shaping user adoption intention of a representative case of controversial IS, namely online dating services (ODS).

The model was tested with two empirical studies using structural equation modeling techniques. The data of these studies were collected from 451 (Study 1) and 510 (Study 2) single individuals (i.e. not in a relationship).

(1) Positive social influence has a stronger impact on perceived benefits and adoption intention, while negative social influence exerts a greater impact on perceived risks; (2) positive and negative social influences affect adoption intention toward ODS differently, through benefit and risk assessments; and (3) ambivalence significantly negatively moderates the effects of social influences on adoption.

This study enriches and extends the IS use, ambivalence theory, prospect theory, and social learning theory research streams. Furthermore, this study suggests that it is necessary to focus on not only the oft-considered positive but also negative social influences in IS research.

The present paper aims to reveal how different cultures, as reflected by cultural norms, traditions, and social expectations, influence food waste behaviour in different regions of the world.

A systematic multifaceted literature review was employed as a main research tool.

The focal role of education and awareness campaigns in reducing household food waste and promoting responsible food consumption behaviours is revealed. The importance of guilt, behavioural control, negative attitudes towards leftovers, and social norms are among the most important factors predicting intentions to reduce food waste. Cultural beliefs significantly shape food attitudes and waste. Tailoring sustainable practices to traditions helps to ensure food security. Embracing cultural diversity can lead to the development of effective and sustainable food consumption patterns across different parts of the world.

To the best of the authors’ knowledge, this is the first paper fully devoted to revealing how different cultural backgrounds shape food consumption habits and which marketing strategies aiming to nudge positive changes in responsible food consumption are preferred in different cultural contexts.

Nowadays, some online retailing platforms emerge to integrate transport capacity to provide standard distribution service for sellers. Such an integrated form of service is defined as delivery alliance (DA). To have a better understanding of how to price the service, this study aims to fixate on the seller’s problems and builds a series of profit maximization models in accordance with the two-sided market pricing theory within a platform business model.

In the present study, some optimization models are built in the two-sided market type and the optimal solutions are found in a three-dimensional decision space. By using the basic model as the benchmark, some optimization problems of DA in realistic situations are discussed. Particularly, a power-law-distribution model is established to deal with the uncertainty in forecasting. Also, a price-sensitive model and a loss-aversion model are presented to describe the various reactions of sellers to charging modes. Finally, some combined situations are discussed and the strategies are compared under the mentioned models.

By selecting the basic model as the benchmark, the specific pricing strategies are found for each context to yield the optimal profits. The flexibility of pricing strategy in the basic model and rigid pricing strategies in extended models, are discussed. As a result, the guidelines for the online retailing platforms are developed on designing and pricing the DA service.

First, it would be interesting to expand the pricing plan of the platform. For instance, menu pricing and quantity discount have not been considered, which are common in practice. The time discounting has also been ignored. If the time value were calculated, the contract fees would be more critical due to the earliest of collecting money. Finally, those joiners who have huge order sizes are crucial for the ecosystem indeed, but arouse no attention. While in reality, they may have more power to bargain with the platform. Thus, how the platform competition affects the pricing strategies needs future research.

The optimal pricing strategies under these models are analytically found out, and it is shown that the presented models result in the same scale of joiners and profits in optimization. This suggests that DA works well in various behavioral contexts. This also suggests that DA is a significant controller in service quality improvement. Then, the optimal pricing strategies are compared among all the models. During this, it is discovered that the realistic contexts might reduce the profit, whereas an appropriate pricing strategy can pull this back without loss of service quality.

This paper aims to study the mixed after-sales service which simultaneously offers return and replacement services. The authors develop a model to propose what kind of after-sales service the firm should choose and how to make the after-sales service policy to improve the profit. The study aims to extend the literature on the mixed after-sales service and give some support to the managers to make decisions.

In this paper, the authors use the optimization modeling method to describe the situations of a firm offering two exclusive after-sales service policies and a mixed after-sales service policy, respectively. They compare the results in different cases and analyze the impact of different parameters on the boundary values and other results. Finally, the authors include three numerical examples to illustrate the major results.

The authors find that the mixed after-sales service can successfully segment the market, meet various customers’ distinct needs and differentiate the service prices to improve the total profit. Moreover, the authors find the boundary values which indicate the optimal interval for each service. Then, for a certain situation, they can clearly tell which after-sales service dominates and provides the optimal selling price, order quantity and total profit. Besides, the authors show the impact of different parameters on the boundary values and other results.

This paper combines after-sales service into traditional models and provides a new mixed service to segment the market and improve total revenue. It provides some managerial implications for the decision-makers.

Social commerce websites have emerged as new platforms which integrate social media features with traditional commerce aspects to enhance users’ purchasing experience. The purpose of this paper is to examine the role of social factors such as trust toward site members in determining users’ trust and risk evaluations, and the role of social commerce use habit in attenuating users’ rational risk and trust considerations for developing purchase intentions.

Relying on the risk deterrence perspective and rational decision-making models involving trust and habit, this study proposes a set of hypotheses which are tested through analyzing survey data using structural equation modeling techniques.

Results show that commerce risk deters purchasing intentions; trust toward the social commerce website increases users’ purchasing intentions; and trust toward the site members indirectly increases purchasing intentions. Moreover, trust toward site members reduces perceived commerce risk. Findings also show that habit modulates trust and risk effects on use decisions in this context; habit moderates (weakens) the relationships between commerce risk and purchase intentions and between trust toward the social commerce site and purchase intentions.

This study extends theories on decision making in social settings such as in the case of social commerce. It does so by accounting for unique modulating effects of habit in social settings in which social aspects such as trust in other members and risk are unique and important.