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Negative brand engagement represents a pervasive and persistent feature of interactivity in online contexts. Although existing research suggests that consumer negativity is potentially more impactful or detrimental to brands than its positive counterpart, few studies have examined negative brand-related cognitions, feelings and behaviours. Building on the concept of brand engagement, this study aims to operationalise negative online brand engagement.

This paper presents the results of nine studies that contributed to the development and validation of the proposed scale. Building on the concept of engagement, Studies 1–3 enhanced the construct conceptualisation and generated items. Study 4 involved validation with an academic expert panel. The process of measure operationalisation and validation with quantitative data was completed in Studies 5–8. Finally, the scale's nomological validity was assessed in Study 9.

The results confirm the multidimensional nature of negative online brand engagement. The validated instrument encompasses four dimensions (cognition, affection, online constructive behaviour and online destructive behaviour), captured by 17 items.

Progress in understanding and dealing with negative online brand engagement has been hampered by disagreements over conceptualisation and the absence of measures that capture the phenomenon. This work enhances managerial understanding of negativity fostering strategies that protect brand engagement and improve firm performance.

This research analyzes online consumer reviews and ratings to assess e-retail order fulfillment performance. The study aims to (1) identify consumer journey touchpoints in the order fulfillment process and (2) determine their relative importance for the consumer experience.

Text mining and analytics were employed to examine over 100 m online purchase orders, along with associated consumer reviews and ratings from Amazon US. Using natural language processing techniques, the corpus of reviews was structured to pinpoint touchpoints related to order fulfillment. Reviews were then classified according to their stance (either positive or negative) toward these touchpoints. Finally, the classes were correlated with consumer rating, measured by the number of stars, to determine the relative importance of each touchpoint.

The study reveals 12 touchpoints within the order fulfillment process, which are split into three groups: delivery, packaging and returns. These touchpoints significantly influence star ratings: positive experiences elevate them, while negative ones reduce them. The findings provide a quantifiable measure of these effects, articulated in terms of star ratings, which directly reflect the influence of experiences on consumer evaluations.

The dataset utilized in this study is from the US market, which limits the generalizability of the findings to other markets. Moreover, the novel methodology used to map and quantify customer journey touchpoints requires further refinement.

In e-retail and logistics, comprehending touchpoints in the order fulfillment process is pivotal. This understanding helps improve consumer interactions and enhance satisfaction. Such insights not only drive higher conversion rates but also guide informed managerial decisions, particularly in service development.

Drawing upon consumer-generated data, this research identifies a cohesive set of touchpoints within the order fulfillment process and quantitatively evaluates their influence on consumer experience using star ratings as a metric.

This study aims to understand the perceived emotions of human–artificial intelligence (AI) interactions in the private sector. Moreover, this research discusses the transferability of these lessons to the public sector.

This research analysed the comments posted between June 2022 and June 2023 in the global open Reddit online community. A data mining approach was conducted, including a sentiment analysis technique and a qualitative approach.

The results show a prevalence of positive emotions. In addition, a pertinent percentage of negative emotions were found, such as hate, anger and frustration, due to human–AI interactions.

The insights from human–AI interactions in the private sector can be transferred to the governmental sector to leverage organisational performance, governmental decision-making, public service delivery and the creation of economic and social value.

Beyond the positive impacts of AI in government strategies, implementing AI can elicit negative emotions in users and potentially negatively impact the brand of private and government organisations. To the best of the authors’ knowledge, this is the first research bridging the gap by identifying the predominant negative emotions after a human–AI interaction.

This study aims to contribute to the darker side of consumer–brand interactions by examining the relationship between consumer-related antecedents, particularly consumer personality traits, in triggering brand-hate emotions. Additionally, the link between brand hate and brand forgiveness was also taken into account, as well as the moderating impact of personality attributes. The impact of brand forgiveness on consumer coping behavior was investigated, particularly for brand switching (flight) and negative word-of-mouth (NWOM) (fight) on Indian e-commerce shopping websites/apps.

Using a structured questionnaire survey and a nonprobability purposive sampling approach, data were obtained from 438 online shoppers who had experienced hate directed at a particular shopping website or app. The hypotheses were tested statistically using partial least squares (PLS) structural equation modeling with SmartPLS 4 software.

First, the findings demonstrate that agreeableness, extraversion and neuroticism significantly affected brand hate. Second, the results indicate that personality traits, particularly extraversion and conscientiousness from the Big-Five model, play a substantial role in moderating the relationship between brand hate and brand forgiveness. Third, the study also reveals the significance of brand forgiveness in mitigating the adverse consequences of NWOM and brand switching in the context of e-commerce platforms.

Practical steps such as complaint-management processes and prompt resolutions through an appropriate means of active interaction and understanding the consumer’s personality when their concerns are heard and handled can help brand managers earn customers’ forgiveness and reduce brand hate toward e-commerce websites/apps.

Based on the authors’ understanding, this study is the initial one to incorporate brand hate, brand forgiveness and coping strategies into the model in a service context with the interaction effect of consumer personality traits.

In online purchase for dietary supplements, due to the lack of professional advice from pharmacists, electronic word-of-mouth (eWOM) has become an important source of information for consumers to make purchase decisions. How can firms use eWOM resources to increase sales? The purpose of this paper is to provide practical methods for firms by exploring the effects of eWOM on sales and developing a sales prediction model based on eWOM.

The data came from 120 dietary supplements on Tmall.com. The authors extracted the product sales as dependent variable and 11 eWOM factors as independent variables. The multicollinearity was tested by using variance inflation factor and least absolute shrinkage and selection operator. The multiple linear regression was used to investigate the effects of eWOM on sales. Drawing on white- and black-box approaches, six models were developed. Comparing the root mean square error, the authors selected the optimal one as their target sales prediction model.

Product ratings, total reviews and favorites are positively and strongly associated with sales. Questions and additional reviews have negative effects on sales. The random forest model has the best prediction performance.

The research focuses on eWOM of dietary supplement. First, the authors show that easily accessible eWOM from online platforms can be used to evaluate effects and predict sales. Second, the authors introduce white- and black-box models through machine learning to assess eWOM. Firms could use the described models to foster their marketing initiatives.

The aims of this study are to analyse the impact of brand-centric relationships (individual and collective) and negative emotions on brand hate felt towards brands used in extreme sports and to assess whether brand hate is a driver of negative consumer behavioural intentions.

This study takes a quantitative approach, using a sample of 300 Spain-based users of snow-sports brands. After validating the measurement scales, the hypotheses were tested through structural equation modelling. Drawing on the cognitive perspective of emotions and the triangular theory of hate, this study posits that individual and collective consumer-brand relationships evoke inward negative emotions and brand hate, thus influencing brand avoidance, brand switching and negative word-of-mouth.

The results showed that collective and individual consumer-brand relationships (negative brand experience, consumer-based brand equity and symbolic incongruence) impact inward negative emotions towards snow-sports brands. Inward negative emotions directly influence brand hate, which in turn affects consumers’ intention to avoid brands, switch brands and engage in negative word-of-mouth.

This research provides novel insights into how individual and collective brand-centric relationships evoke inward negative emotions towards extreme sports’ brands, which in turn increases brand hate, and expands knowledge of how brand hate might increase the consumer’s intentions to avoid the brand, intention to switch brands and intention to engage in negative word-of-mouth.

Studies on the negative aspects of consumer–brand relationships have received increasing attention in academia, but most research on this phenomenon is not focused on services. On the other hand, the literature consistently demonstrates evidence that gender affects consumer behavior. In this context, this study aims to unprecedentedly identify the antecedents of brand hate and the effects of consumer gender across different service sectors.

This research compares the results of two studies with service companies. The first was accomplished with 307 consumers of mobile phone operators, and the second study was performed on 450 higher education students. The data were analyzed using structural equation modeling.

In both studies, females showed greater importance for ideological incompatibility than males. This suggests that females are more sensitive to moral issues and ethical behavior than males. As for males, negative experience is the most relevant antecedent of brand hate in both samples. However, when age is checked, the results indicate that younger males develop more brand hate than older males. This does not happen with females.

This study demonstrates gender differences and compares two samples applied in different service sectors: low-technological and high-touch consumer interactions. The results show that the antecedents of brand hate for males and females in the service sector differ. This study also points out that older males present a different behavior when compared to younger males, which does not happen with females.

The purpose of this study is to assist brand and product managers in selecting appropriate ingredient names for environmentally friendly products. It investigates the effects of unfamiliar ingredients on consumers’ evaluations of environmental friendliness and their purchase intentions, based on the cue consistency theory.

Five experimental studies (n = 968) were conducted to achieve the research objectives. Study 1 found that consumers tended to avoid choosing unfamiliar ingredients. Study 2 examined the impact of ingredient familiarity on consumers’ perceived greenness. Study 3 investigated the mediating role of perceived naturalness. Studies 4 and 5, respectively, explored the moderating effects of emphasizing the importance of technology in environmental conservation and product category.

The findings indicate that when environmentally friendly products are labeled with unfamiliar ingredients (vs. familiar), consumers’ perceived greenness and purchase intentions decrease. This effect is mediated by perceived naturalness. Moreover, the negative impact of unfamiliar ingredients is mitigated by emphasizing the importance of technology and the high-tech product category.

This paper reveals the unique role of unfamiliar ingredients in shaping consumer attitudes toward environmentally friendly products. Based on cue consistency theory, it uncovers how unfamiliar ingredients influence the perceived greenness of environmentally friendly products through perceived naturalness. Furthermore, the paper demonstrates the impact of emphasizing the importance of technology (emphasis vs. control) and product category (high-tech vs. low-tech) on consumer attitudes and behaviors toward environmentally friendly products.

The purpose of this study is to develop an integrated conceptual framework to better understand the psychological pathways connecting consumer perceptions to purchasing intentions for premium sustainable products.

The study develops a conceptual model that theorizes relationships between consumer perceptions of a firm’s innovation, competitive advantage, sustainable practices and stakeholder orientation. It proposes that stakeholder orientation mediates the effects of these perceptions on consumers’ willingness to purchase premium sustainable products. Additionally, lifestyle is hypothesized as a moderator. The model advances knowledge through eight testable propositions.

The conceptual framework specifies indirect, mediated and moderated relationships that have not been fully captured by past literature. It theorizes that perceptions of a firm’s innovation, competitive advantage from sustainable practices and stakeholder orientation indirectly influence purchase willingness through the mediating role of stakeholder orientation. Lifestyle is proposed to moderate these relationships.

This conceptual model offers insights for cultivating consumer perceptions that strengthen a firm’s stakeholder image and endorsement of premium sustainable products. Its validated theoretical lens and propositions can provide strategic guidance for addressing the challenges of higher price points for sustainable products through capturing psychological drivers of values-based decision-making. Future empirical assessment is recommended to validate the specified relationships in the model.

This study examined brand hate within the context of the (German) Bundesliga and (Australian) National Rugby League (NRL). The study pursued two research questions: (1) What types of brand hate were expressed towards the Bundesliga and the NRL? (2) To what extent did hateful comments attract more likes than non-hateful comments?

Brand hate was studied in the context of competition restrictions in 2020 due to the Covid-19 pandemic. We analysed reader comments posted below online articles published in three German (119 articles and 8,975 comments) and three Australian online newspaper articles (116 articles and 4,858 reader comments). The data were analysed deductively.

Non-parametric tests found that all types of brand hate were expressed. Approximately 85% of the hateful comments were mild, or more specifically, cold (n = 445 or approximately 53%), or cool (n = 250 or approximately 30%), or hot (n = 20 or approximately 2%). Hateful comments attracted more likes than non-hateful comments.

This study advances our understanding of how negative brand perceptions underpin an extreme negative emotional reaction in the form of brand hate. The empirical evidence enables brand managers to better address disgusted, angry, or contemptuous consumers (or stakeholders) and consider whether the feeling is enduring, strong or weak, and linked to either aggressive or passive behaviours.