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Brands are increasingly reflecting social values, and many brands have begun to embrace equality and inclusivity as a marketing strategy. Accordingly, consumers are increasingly being exposed to brands associated with different social groups. This paper aims to examine how consumers who have experienced pride respond to brands associated with dissociative out-groups.

Four studies were conducted. Study 1 tested the basic effect of how the experience of different facets of pride affects consumers’ brand attitudes toward a brand associated with a dissociative out-group. Studies 2 and 3 examined the underlying mechanism of consumers’ psychological endorsement of egalitarianism using both mediation and moderation approaches. Study 4 derived implications of our findings for marketers.

The results show that consumers respond differently to a brand associated with a dissociative out-group based on the facets of pride they experience. When consumers experience authentic (vs hubristic) pride, they exhibit a more favorable attitude toward the brand associated with the dissociative out-group. This is because authentic (vs hubristic) pride increases consumers’ psychological endorsement of egalitarianism, which enhances consumers’ brand attitudes toward the brand associated with the dissociative out-group.

The findings suggest that brand managers should think about ways to elicit consumers’ authentic pride to minimize the potential backlash from consumers when promoting equality and inclusivity in their brand communications, particularly when such communications contain cues of dissociative out-groups.

This paper contributes to the branding literature by identifying pride as an important determinant that can help brands overcome the negative impact of dissociative out-groups on consumers’ brand reactions, enriches the literature on pride by documenting a novel effect of the two facets of pride on consumer behavior and extends the literature of egalitarianism by demonstrating pride as a driver of consumers’ psychological endorsement of egalitarianism.

Despite the increasingly common view that online brand community (OBC) members are heterogeneous, knowledge concerning the impact of group heterogeneity on community and brand level outcomes is lacking. In response and drawing from organization research, this paper aims to study the consequences of two types of group heterogeneity (i.e. visible heterogeneity and value heterogeneity) on brand community commitment and brand commitment. The moderating role of tenure in a community is also examined.

A survey of 467 members of OBCs was conducted, and structural equation modeling was used to test hypotheses.

The results show that perceived visible heterogeneity positively affects brand community commitment, whereas perceived value heterogeneity has a negative effect on it. Brand community commitment positively relates to brand commitment; it also mediates the effect of perceived visible heterogeneity and perceived value heterogeneity on brand commitment. Further, the positive effect of visible heterogeneity on brand community commitment is stronger for short-tenure members, but the negative effect of value heterogeneity is stronger for long-tenure members.

The findings suggest that managers should make efforts to foster visible heterogeneity and reduce value heterogeneity. In addition, managers are advised to emphasize the characteristics that carry different appeal for members of different tenure.

This research is one of the first few quantitative studies to examine the influence of brand community heterogeneity on community, and especially brand level outcomes. It extends the literature on the effect of brand community on brands and adds to the emerging heterogeneity view of OBCs.

In an online brand community (OBC), consumers as a group occupy a dominant position, and their horizontal interactions are pivotal for the consumer–brand relationship. However, little is known about the effect of group characteristics on brands. To partially fill this gap, this study examines how group characteristics influence brand loyalty from the perspective of social identity theory. Specifically, by collecting data from an online survey, this paper investigates the effects of group similarity, group receptivity and group involvement on brand loyalty, the mediating role of community identification and the moderating effect of tenure in a community.

Data from 482 brand community members were analyzed using structural equation modeling.

The results show that group similarity, group receptivity and group involvement increase brand loyalty; furthermore, the effect is mediated by community identification. Moreover, group receptivity is more effective in fostering community identification of short-tenure members, whereas group similarity plays a more important role for long-tenure members.

This paper enriches the brand community literature from a group perspective and provides implications for how brand communities develop customer loyalty strategies.

Contracts and trust are two prominent governance mechanisms in buyer–supplier exchanges, yet controversy persists regarding the interplay between contracts and trust. This study aims to provide a new perspective to understand the debate by differentiating between- from within-dyad effects of contracts–trust relationships.

Based on survey data of 250 Chinese buyer–supplier relationships collected over two time periods, this study used two-level hierarchical linear modeling (HLM) with repeated measures to test the influence of contracts (trust) on trust (contracts) over time.

The authors find that for major buyer–supplier exchanges, contracts and trust tend to complement each other when comparing across dyads, but they likely substitute for each other in within-dyad settings.

First, to illustrate the dynamic interactions between contracts and trust, this study collected data at two time periods and assumed continuous linear relationships of time with both contracts and trust. Further research should collect multiple waves of data to explore the complex, varying changes that arise over time. Second, this study’s findings are based on buyer–supplier relationships in China, whose unique cultural features may limit the generalizability of the results to other settings.

Channel managers can structure exchanges by devising detailed contracts that align incentives and demonstrate commitment, which helps build trust in a relationship. Channel managers should also pay special attention to the contingency effects of their transactional and relational features.

This study offers the first explicit test of the dynamic contracts–trust relationship, thereby establishing a more refined understanding of interplay between contracts and trust.

Given the pivotal influence of institutional forces, an important yet underexplored question in supply chain management literature is how contractual and relational governance jointly affect supplier performance under weak legislative environments. This study tends to solve the debate by distinguishing contractual definability from contractual enforceability and by considering the contingent role of legal development in China.

Using a combined dataset of secondary data and a survey of 224 buyer–supplier dyads in China, this study examines how contractual definability and contractual enforceability interact with relational governance differently in driving supplier performance, and assesses the contingent role of legal development.

This study finds that contractual definability complements yet contractual enforceability substitutes relational governance in affecting supplier performance. Moreover, legal development weakens the complementary effect but strengthens the substitutive effect.

The study firstly enriches supply chain management literature by classifying the roles of contracts into contractual definability and contractual enforceability and showing their differential interplay with relational governance. Second, the study contributes to the complements–substitutes debate by revealing the shifting role of legal development. Third, the research enriches the understanding of supply chain management in the Chinese market.

This paper studies how multichannel retailers choose the product quality level and decide which attribute to make prominent in their physical store in a competitive environment.

This paper develops a game theoretic model, in which multichannel retailers' decisions are made in three stages. Using prominent experiential attributes (e.g. functionality) in their offline store and product quality decisions, multichannel retailers are capable of transferring the sales between different channels.

This analysis shows that making different attributes prominent in their physical store may be an equilibrium, and each multichannel retailer chooses the highest quality level for the prominent attribute. However, the prominent attribute of the highest quality level is not always optimal. Under certain conditions, multichannel retailers may make the experiential attribute prominent in their respective physical stores, which can result in equilibrium.

The results indicate that multichannel retailers should avoid blindly highlighting high-quality attributes in a competitive environment, or falling into price completion.

From the perspective of prominent attributes, this study designs the optimal product line based on channel characteristics. The results of the research can provide practical implications for multichannel retailers to increase sales.

This study aims to examine the relationship between consumers’ emotional expressions and their self-construals. The authors suggest that because an independent self-construal can reinforce the free expression of emotion, the expression of extreme emotions is likely to become associated with feelings of independence through social learning.

The paper includes five studies. Study 1A provided evidence that priming participants with different types of self-construal can influence the extremity of their emotional expressions. Study 1B showed that chronic self-construal could predict facial expressions of students who were told to smile for a group photograph. Studies 2–4 found that inducing people to either manifest or to simply view an extreme facial expression activated an independent social orientation and influenced their performance on tasks that reflect this orientation.

The studies provide support for a bidirectional causal relationship between individuals’ self-construals and the extremity of their emotional expressions. They show that people’s general social orientation could predict the spontaneous facial expressions that they manifest in their daily lives.

Although this research was generally restricted to the effects of smiling, similar considerations influence the expression of other emotions. That is, dispositions to exhibit extreme expressions can generalize over different types of emotions. To this extent, expressions of sadness, anger or fear might be similarly associated with people’s social orientation and the behavior that is influenced by it.

The paper provides marketing implications into how marketers can influence consumers’ choices of unique options and how marketers can assess consumers’ social orientation based on their observation of consumers’ emotional expressions.

To the best of the authors’ knowledge, this research is the first to demonstrate a bidirectional causal relationship between individuals’ self-construals and the extremity of their emotional expressions, and to demonstrate the association between chronic social orientation and emotional expression people spontaneously make in their daily lives.

The purpose of this paper is to investigate the conditions under which working with an incumbent downstream competitor could be a beneficial strategy for upstream firms as the case of the relationship between banks and third-party payment providers.

Using a game model, this study considers a market with two upstream firms (banks) and two downstream firms (third-party payment providers). One downstream firm is an incumbent that poses a competitive threat to the upstream market, and the other downstream firm does not.

The results show that the optimal decision for banks depends on the number of loyal users the incumbent third-party payment providers and banks have. When the bank has more loyal users than the competitive third-party provider to a certain level, it would terminate cooperation with the provider; otherwise, the bank would maintain cooperation. This is true whether the duopoly banks are symmetrical or asymmetrical.

This study makes contribution to the theory of co-opetition lies in the fact that it examines a special case of competition and cooperation between vertical enterprises in the bank context. This study investigates how the upstream firms do when threatened by a downstream firm while the upstream firms have other options. This study also contributes to bank marketing theory through providing explanations for some of the incomprehensible cooperation in China's payment market, which is characterized by consumer loyalty. This study extends previous new-entry competition for banks by differentiating between incumbent and new-entry downstream firms.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJBM-11-2019-0414

The purpose of this study is to achieve an accurate intelligent fault diagnosis of rolling bearing.

To extract deep features of the original vibration signal and improve the generalization ability and robustness of the fault diagnosis model, this paper proposes a fault diagnosis method of rolling bearing based on multiscale convolutional neural network (MCNN) and decision fusion. The original vibration signals are normalized and matrixed to form grayscale image samples. In addition, multiscale samples can be achieved by convoluting these samples with different convolution kernels. Subsequently, MCNN is constructed for fault diagnosis. The results of MCNN are put into a data fusion model to obtain comprehensive fault diagnosis results.

The bearing data sets with multiple multivariate time series are used to testify the effectiveness of the proposed method. The proposed model can achieve 99.8% accuracy of fault diagnosis. Based on MCNN and decision fusion, the accuracy can be improved by 0.7%–3.4% compared with other models.

The proposed model can extract deep general features of vibration signals by MCNN and obtained robust fault diagnosis results based on the decision fusion model. For a long time series of vibration signals with noise, the proposed model can still achieve accurate fault diagnosis.

The purpose of this study is to analyze the intelligent semisupervised fault diagnosis method of aeroengine.

A semisupervised fault diagnosis method based on denoising autoencoder (DAE) and deep belief network (DBN) is proposed for aeroengine. Multiple state parameters of aeroengine with long time series are processed to form high-dimensional fault samples and corresponding fault types are taken as sample labels. DAE is applied for unsupervised learning of fault samples, so as to achieve denoised dimension-reduction features. Subsequently, the extracted features and sample labels are put into DBN for supervised learning. Thus, the semisupervised fault diagnosis of aeroengine can be achieved by the combination of unsupervised learning and supervised learning.

The JT9D aeroengine data set and simulated aeroengine data set are applied to test the effectiveness of the proposed method. The result shows that the semisupervised fault diagnosis method of aeroengine based on DAE and DBN has great robustness and can maintain high accuracy of fault diagnosis under noise interference. Compared with other traditional models and separate deep learning model, the proposed method also has lower error and higher accuracy of fault diagnosis.

Multiple state parameters with long time series are processed to form high-dimensional fault samples. As a typical unsupervised learning, DAE is used to denoise the fault samples and extract dimension-reduction features for future deep learning. Based on supervised learning, DBN is applied to process the extracted features and fault diagnosis of aeroengine with multiple state parameters can be achieved through the pretraining and reverse fine-tuning of restricted Boltzmann machines.