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Previous research suggests that self-presentation causes people to have a reflective tendency to produce electronic word-of-mouth (eWOM). Drawing on the theory of the reflective-impulsive model (RIM), this paper aims to examine whether self-presentation also could motivate an impulsive tendency to produce eWOM. Self-monitoring is suggested as a possible moderator in the relationship between self-presentation and impulsive eWOM production.

Data were collected based on an online survey of members from a consumer panel. The effective sample size was 574 respondents. Structural equation modeling (SEM) was used to analyze the data.

The findings show that self-presentation may drive both impulsive and reflective eWOM tendencies; however, that the relationship between self-presentation and impulsive eWOM tendency is contingent on high levels of self-monitoring.

By including self-monitoring as a moderator, this study is the first to show a relationship between self-presentation and impulsive eWOM production. Moreover, the findings show that both impulsive and reflective eWOM tendencies are associated with an enhanced tendency to produce eWOM, thereby demonstrating the usefulness of the RIM theory in understanding eWOM behavior. Overall, the findings shed light on how companies may stimulate eWOM production, and consequently provide insight into creating more effective eWOM campaigns.

Consumers often communicate with other consumers and perform impulse buying behavior on social commerce websites. Based on stimulus-organism-response framework and dual systems theory, the present study examines the effects of social interactions and self-control on consumers' impulse purchase.

An online survey consisting of 315 participants on social commerce websites was recruited to empirically examine the proposed research model. Partial Least Squares (PLS) was employed to analyze the research model.

Our main findings indicate that (1) source credibility, observational learning and review quality are important antecedents of perceived usefulness of online reviews, (2) source credibility, observational learning and perceived usefulness positively affect positive affect, which further results in urge to buy and impulse buying, (3) self-control weakens the effect of positive affect on urge to buy impulsively and also weakens the effect of urge to buy impulsively on impulse buying behavior.

The present study will bring more attention to social interactions in social networks in practice and encourage scholars to pay more attention to the reflective system in online impulse buying.

Immersive virtual reality (IVR) has been frequently proposed as a promising tool for learning. However, researchers have commonly implemented a plethora of design elements in these IVR systems, which makes the specific aspects of the system that are necessary to achieve beneficial outcomes unclear. Against this background, this study aims to combine the literature on presence with learning theories to propose that the ability of IVR to present 3D objects to users improves the presence of these objects in the virtual environment compared with 2D objects, leading to increased learning performance.

To test this study’s hypotheses, the authors conducted a 2 (training condition: approach vs avoid) x 2 (object presence: high vs low) between-subjects laboratory experiment that used IVR with 83 female participants.

The results support this study’s hypotheses and show that training with high object presence leads to greater reactions to cues (chocolate cravings) and improved health behaviour (chocolate consumption).

This study shows that increased object presence leads to unique experiences for users, which help reinforce training effects. Moreover, this work sheds further light on how immersive computer technologies can affect user attitudes and behaviour. Specifically, this work contributes to IVR research by showing that learning effects can be enhanced through an increased degree of object presence.

Integrating the two‐system (reflective vs. impulsive) model and the “stimulus‐organism‐response” framework, the purpose of this paper is to construct and empirically test a model that examines online impulse buying as a phenomenon triggered by system design factors.

A laboratory experimental design with a 2×2 full factorial design involving 151 undergraduate students was used to validate the effects of system design stimuli on online impulse buying. Interactivity and vividness, two design factors, were manipulated and a fictitious VCD movie store was created, with four storefronts representing each combination of treatments.

A compelling and sociable virtual experience as conceptualized with telepresence and social presence has a significant effect on buying impulses over and above traditional marketing/product stimuli. Such virtual experience can be created through the usage of interactive and vivid website features. Furthermore, cognition positively moderates the relationship between buying impulse and the actual purchasing behavior.

The findings provide valuable guidance in website design that can stimulate online impulse buying. The results also indicate the importance of providing cognitive intervention at the purchasing stage.

A significant extension of the “stimulus‐organism‐response” framework is to introduce presence as the system stimulus that captures the overall virtual experience and to specify the associated design features; i.e. interactivity and vividness. By incorporating the two‐system model, this study offers a theoretical underpinning of the role of cognitive processing in impulse buying.

Business and academia alike have become aware of the crucial role of customer‐to‐customer interactions. Facilitated by the increasing customer connectedness through online media possibilities, companies need to understand how customers influence each other and how to manage these customer interactions. The purpose of this paper is to conceptualize an expanded model of customer‐driven influence (CDI) that presents an overview of the influence process and its determinants. The model covers important issues, such as deliberate versus unintentional sender actions, verbal and non‐verbal communication, and reflective and impulsive receiver reactions.

This article is the result of the first Thought Leadership Conference on Service Marketing, held in Nijmegen, The Netherlands, June 2012.

The model shows the importance of considering goal theory in studying customer‐driven influence. Both sender and receiver can act and react in deliberate and unintentional ways. The mechanisms for customer‐driven influence are then contingent upon which particular goal (combination) is activated. Message reception is either verbal or non‐verbal. Furthermore, the receiver can react either by reflective processing or by impulsive processing leading to liking a particular product or wanting the product (respectively). Accordingly, the receiver builds behavioral intentions of purchasing and further talking about the particular product.

This paper synthesizes insights from the extant literature on word‐of‐mouth, social influence, and dual processing of information to develop a comprehensive model customer‐driven influence. The authors' framework is embedded in goal system theory, as it addresses fundamental self‐regulatory issues, such as the impact of implicit goal activation and essential contextual factors on preference formation and choice.

The purpose of this study is to examine how consumer personality trait impulsiveness influences trustworthiness evaluations of online-offers with different trust-assuring and trust-reducing elements by measuring the brain activity of consumers. Shoppers with high degrees of impulsiveness are referred to as hedonic shoppers, and those with low degrees are referred to as prudent consumers.

To investigate the differences between neural processes in the brains of hedonic and prudent shoppers during the trustworthiness evaluation of online-offers, the present study used functional magnetic resonance imaging (fMRI) and region-of-interest analysis to correlate neural activity patterns with behavioral measures of the study participants.

Drawing upon literature reviews on the neural correlates of both trust in online settings and consumer impulsiveness and using an experimental design that links behavioral and fMRI data, the study shows that consumer impulsiveness can exert a significant influence on the evaluation of online-offers. With regard to brain activation, both groups (hedonic and prudent shoppers) exhibit similar neural activation tendencies, but differences exist in the magnitude of activation patterns in brain regions that are closely related to trust and impulsiveness such as the dorsal striatum, anterior cingulate, the dorsolateral prefrontal cortex and the insula cortex.

The data provide evidence that consumers within the hedonic group evaluate online-offers differently with regard to their trustworthiness compared to the prudent group, and that these differences in evaluation are rooted in neural activation differences in the shoppers’ brains.

Marketers need to be made aware of the fact that neurological insights can be used for market segmentation, because consumers’ decision-making processes help explain behavioral outcomes (here, trustworthiness evaluations of online-offers). In addition, consumers can learn from an advanced understanding of their brain functions during decision-making and their relation to personal traits such as impulsiveness.

Considering the importance of trust in online shopping, as well as the fact that personality traits such as impulsiveness influence the purchase process to a high degree, this study is the first to systematically investigate the interplay of online trustworthiness perceptions and differences in consumer impulsiveness with neuroscientific methods.

The purpose of this paper is to propose a fuel‐optimal virtual centre selection method for formation flying maintenance in the J2 perturbed environment.

Based on the relative orbital elements (ROE) theory, the J2 perturbed relative motions between different satellites in the formation are analyzed, and then the fuel‐optimal virtual centre selection issue for formation flying maintenance are parameterized in terms of ROE. In order to determine the optimal virtual centre, two theories are proposed in terms of ROE.

Numerical simulations demonstrate that the fuel‐optimal virtual centre selection method is valid, and the control of the ROE of each satellite with respect to a virtual optimal centre of the formation is more efficient regarding the fuel consumption than the control of all satellites with respect to a satellite belonging to the formation.

The fuel‐optimal virtual centre selection method is valid for formation flying mission whose member satellite in circular or near circular orbit.

The fuel‐optimal virtual centre selection approach can be used to solve formation flying maintenance problem which involves multiple satellites in the formation.

The paper proposes a fuel‐optimal virtual centre selection method in terms of ROE, and shows that keeping the formation with respect the optimal virtual centre is more fuel efficient.

A good decision support system for credit scoring enables telecom operators to measure the subscribers' creditworthiness in a fine-grained manner. This paper aims to propose a robust credit scoring system by leveraging latent information embedded in the telecom subscriber relation network based on multi-source data sources, including telecom inner data, online app usage, and offline consumption footprint.

Rooting from network science, the relation network model and singular value decomposition are integrated to infer different subscriber subgroups. Employing the results of network inference, the paper proposed a network-aware credit scoring system to predict the continuous credit scores by implementing several state-of-art techniques, i.e. multivariate linear regression, random forest regression, support vector regression, multilayer perceptron, and a deep learning algorithm. The authors use a data set consisting of 926 users of a Chinese major telecom operator within one month of 2018 to verify the proposed approach.

The distribution of telecom subscriber relation network follows a power-law function instead of the Gaussian function previously thought. This network-aware inference divides the subscriber population into a connected subgroup and a discrete subgroup. Besides, the findings demonstrate that the network-aware decision support system achieves better and more accurate prediction performance. In particular, the results show that our approach considering stochastic equivalence reveals that the forecasting error of the connected-subgroup model is significantly reduced by 7.89–25.64% as compared to the benchmark. Deep learning performs the best which might indicate that a non-linear relationship exists between telecom subscribers' credit scores and their multi-channel behaviours.

This paper contributes to the existing literature on business intelligence analytics and continuous credit scoring by incorporating latent information of the relation network and external information from multi-source data (e.g. online app usage and offline consumption footprint). Also, the authors have proposed a power-law distribution-based network-aware decision support system to reinforce the prediction performance of individual telecom subscribers' credit scoring for the telecom marketing domain.

Passivity theory is closely related to both electrical network and circuit analysis methods. The purpose of this paper is to try to establish some basic results on the uncertain discrete‐time fuzzy systems.

Applying the classical and effective Lyapunov function method and the powerful linear matrix inequality toolbox in MATLAB, the paper provides some sufficient conditions to verify the passivity of the uncertain discrete‐time fuzzy systems, or to passify such a system.

For uncertain discrete‐time fuzzy systems, its passivity can be easily verified numerically, and its passification can also be fulfilled.

A very effective and convenient criterion is provided to test the passivity of practical nonlinear discrete‐time system or to passify it.

This paper first treats this topic on uncertain discrete‐time fuzzy systems and obtains some important results.