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This research aims to investigate the role of consumer resistance (CR), display advertising context, appeal and type of exposure for the successful launch of a brand into a new market.

To accomplish this goal, two experiments manipulated the digital context of advertising (congruent vs. incongruent), the advertising appeal (emotional vs. informative) and the type of exposure (incidental vs. forced) using an energy drink brand. In Study 1, data were collected from 80 participants using eye-tracking and an online questionnaire. In Study 2, a total of 138 participants visited a website with the targeted display ad and responded to an online questionnaire.

Overall, the results of two studies show that the relationship between CR and display advertising effectiveness is moderated by the advertising context and advertising appeal in incidental exposure, whereas only the advertising context moderates this relationship in forced exposure when launching a brand into a new market. Moreover, the study illustrates the importance of collecting subjective and objective data in advancing the knowledge and understanding of interactive marketing communications such as display advertising.

The study is a novel attempt within the well-established realm of interactive marketing and, specifically, of digital advertising to examine the persuasive effects of display ad features such as the context, appeal and exposure on display ad effectiveness, considering consumers' predispositions such as resistance to change.

This study examines how consumers' self-construal moderates consumers' buying behavior in situations requiring consumers to buy larger-than-expected clothing sizes. The authors explore the potential effectiveness of two distinct communication strategies – emotional versus informational ad appeals – to mitigate the negative effects of sizing discrepancies.

A total of three experiments were conducted to examine the proposed framework. Studies 1 and 2 investigate whether self-construal moderates the relationship between sizing discrepancy and purchasing intentions. Study 3 examines the effectiveness of communication strategies in reducing the detrimental effects of sizing discrepancy.

When encountering sizing discrepancies, the authors find that consumers with an interdependent self-construal have lower purchase intentions than those with an independent self-construal. The authors demonstrate that an emotional communication strategy is more effective for consumers with an interdependent self-construal, whereas an informational communication strategy is more effective for consumers with an independent self-construal.

With the lack of a universal sizing system, consumers often struggle to find clothes that fit as expected. However, extant research has not explored cross-cultural differences in how consumers respond to sizing discrepancies and how managers can reduce any potential negative effects.

Property developers identify the vital role of social media brand engagement (SMBE) in sustaining their businesses in competitive marketplaces, but it remains underexplored. This paper examines how SMBE mediates the effects of firm-generated content (FGC) and user-generated content (UGC) on brand trust, considering the moderating effects of social media influencer endorsement (SMIE) and self-image congruence (SIC) for luxury residential properties (LRPs).

Around 516 high-income homebuyers in Vietnam who shared information about LRP on social media were targeted to test the research model empirically. The primary data collected from paper-based surveys were analysed using SPSS 26 and AMOS 24.

Results indicate that FGC and UGC positively impact SMBE and consequently significantly affect brand trust. Further, results confirm the moderating roles of SMIE and SIC in the effects of FGC and UGC on SMBE.

Data and sample size were limited to meet the generalisation from different nations and cross cultures.

The authors' findings suggest that marketers should apply the authors' integrated SMBE model to strengthen brand–consumer interactions and increase their sales revenue.

This study is the first in its application of the uses and gratifications theory and self-congruence theory to investigate how SMBE mediates the relationship between FGC and brand trust as well as between UGC and brand trust. Noticeably, this study makes a novel contribution as the first to quantitatively explore the moderating effects of SMIE and SIC in the authors' research model.

This study aims to explore the role of the linguistic style used in the brand-posted social media content on consumer engagement in the Fintech domain.

A total of 3,286 tweets (registering nearly 1.35 million impressions) published by 10 leading Fintech unicorns in India were extracted using the Twitter API. The Linguistic Inquiry and Word Count (LIWC) dictionary was used to analyse the linguistic characteristics of the shared tweets. Negative Binomial Regression (NBR) was used for testing the hypotheses.

This study finds that using drive words and cognitive language increases consumer engagement with Fintech messages via the central route of information processing. Further, affective words and conversational language drive consumer engagement through the peripheral route of information processing.

The study extends the literature on brand engagement by unveiling the effect of linguistic features used to design social media messages.

The study provides guidance to social media marketers of Fintech brands regarding what content strategies best enhance consumer engagement. The linguistic style to improve online consumer engagement (OCE) is detailed.

The study’s findings contribute to the growing stream of Fintech literature by exploring the role of linguistic style on consumer engagement in social media communication. The study’s findings indicate the relevance of the dual processing mechanism of elaboration likelihood model (ELM) as an explanatory theory for evaluating consumer engagement with messages posted by Fintech brands.

Adopting a brand prominence perspective, this study aims to examine how textual and visual brand elements influence the success of crowdfunding campaigns for aftermarket offerings.

A Python-based Web scraper was used to collect data from 620 crowdfunding campaigns for aftermarket offerings hosted on Kickstarter. The linguistic inquiry and word count application programing interface was then used to analyze the linguistic aspects of these campaigns. A fixed effects regression model was used to evaluate the hypotheses.

Textual and visual brand prominence are positively associated with campaign success. Further, with some variations, both types of brand prominence augment the positive effects of narrative and graphic design elements on campaign success.

This study makes novel theoretical contributions to the literature on branding, crowdfunding and aftermarket products. The results also provide practical insights to aftermarket enterprises on creating compelling crowdfunding campaigns.

By analyzing the direct and synergistic effects of branding, narrative and graphic design elements on crowdfunding success, this study extends various literature streams and identifies several future research opportunities.

Given the importance of the growing segmentation of ageing consumers and their increasing interaction with the Internet, digital marketing scholars are becoming more interested in this market. Prior research needs to pay more attention to this market in many contexts of digital marketing. This study aims to provide insights into ageing consumers’ content usage, content typology choices, and online brand advocacy (OBA).

Semi-structured interviews were applied, and 16 consumers from Southern Europe aged 55+ were included. The interviews were transcribed and examined following the principles of content analysis.

According to the research, older consumers display their usage and concerns regarding online content. They have different decision-making processes depending on whether they are purchasing products or services. Likewise, their choices of content typology vary based on the utilitarian or hedonic product category.

This study contributes to the literature by providing insights into this growing segmentation and proposing an OBA framework for older consumers related to content marketing. Finally, the study suggests that older consumers are passive online and active offline brand advocates.

Facilitated by image retouch tools, social media influencers can digitally enhance their self-image in product recommendation posts. This paper proposes that image enhancement may serve as a cue for the audience to assess the authenticity of the influencer (“true to oneself”), which further affects the influencer's product recommendation effectiveness (i.e. attitudes toward the post and recommended product).

Experiment 1 examines the effect of image enhancement on consumers' perceived influencer authenticity and product recommendation effectiveness. Experiment 2 considers the moderating role of post type, examining the effects in informational versus storytelling posts.

Consumers perceived an influencer to be more authentic when the image is not enhanced; in turn, consumers reported more favorable attitudes toward the post and the recommended product upon reading the post. The effects are moderated by post type: the effect of image enhancement (through perceived influencer authenticity) exists in posts using an informational message format but is attenuated for those using a storytelling message format.

This research enriches the literature on authenticity cues by documenting a novel visual cue and contributes to influencer marketing by identifying a nuanced interactive effect between image enhancement and post type on recommendation effectiveness.

This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics.

This study gathers a large Twitter dataset comprising political discussions across various topics from general users. It utilizes an unsupervised machine learning algorithm with pre-defined language features to detect language styles in political discussions on Twitter. Furthermore, it employs a multinomial model to explore the relationships between language styles and users' online characteristics.

Through the analysis of over 700,000 political tweets, this study identifies six language styles: mobilizing, self-expressive, argumentative, narrative, analytic and informational. Furthermore, by investigating the covariation between language styles and users' online characteristics, such as social connections, expressive desires and gender, this study reveals a preference for an informational style and an aversion to an argumentative style in political discussions. It also uncovers gender differences in language styles, with women being more likely to belong to the mobilizing group but less likely to belong to the analytic and informational groups.

This study provides insights into the psychological mechanisms and social statuses of users who adopt particular language styles. It assists political communicators in understanding their audience and tailoring their language to suit specific contexts and communication objectives.

This study reveals gender differences in language styles, suggesting that women may have a heightened desire for social support in political discussions. It highlights that traditional gender disparities in politics might persist in online public spaces.

This study develops a computational methodology by combining cluster analysis with pre-defined linguistic features to categorize language styles. This approach integrates statistical algorithms with communication and linguistic theories, providing researchers with an unsupervised method for analyzing textual data. It focuses on detecting language styles rather than topics or themes in the text, complementing widely used text classification methods such as topic modeling. Additionally, this study explores the associations between language styles and the online characteristics of social media users in a political context.

This study examines the direct impact of justice perceptions of performance appraisal practices (procedural, distributive, interpersonal and informational justice) on job satisfaction, intention to stay and job engagement. Further, it investigates the effect of job engagement on job satisfaction and intention to stay. Moreover, the study tests the mediating role of job engagement on the impact of justice perceptions of performance appraisal practices on job satisfaction and intention to stay.

A total of 650 self-report structured questionnaires were distributed among the employees of 50 information technology companies, and 503 samples were received. Partial least square-structural equation modeling was used to test the hypothesized model.

This study revealed that justice perception of performance appraisal practices positively affects job satisfaction, intention to stay and job engagement. In addition, job engagement positively affects job satisfaction and intention to stay. Further, job engagement significantly transfers the impact of justice perceptions of performance appraisal practices on job satisfaction and intention to stay, thus confirming the mediating role of job engagement. However, the significant direct impact of justice perceptions of performance appraisal practices on job satisfaction and intention to stay in the presence of a mediator, i.e. job engagement, revealed partial mediation.

The findings of this study augment the social exchange theory by explicating that an individual who perceives justice in performance appraisal practices is likely to have greater job engagement, which ultimately leads to higher job satisfaction and intention to stay. This study filled the research gap by examining the role of four justice components of performance appraisal practices on job satisfaction and intention to stay and the mediating role of job engagement in transferring the impact of justice perceptions of performance appraisal practices on job satisfaction and intention to stay.

This study showed the importance of four justice components of performance appraisal practices in enhancing employee job engagement. Hence, this study would motivate information technology companies to maintain fairness in performance appraisal practices to enhance employee job engagement and ultimately increase job satisfaction and intention to stay.

This study is one of its kind that tested the direct impact of comprehensive justice components (procedural, distributive, interpersonal and informational justice) of performance appraisal practices on job satisfaction and intention to stay. In addition, this is a unique study that examined the mediating effect of job engagement on the impact of justice perceptions of performance appraisal practices on job satisfaction and intention to stay.

Live streaming commerce becomes increasingly popular, and some special shopping behaviors existing in traditional e-commerce also emerge in this new context. The current research mainly focuses on determinants of compulsive buying in live streaming commerce by taking fear of missing out (FOMO) and social influence into account.

Using the data collected from 242 experienced consumers in live streaming commerce, the proposed model was empirically assessed by partial least squares based structural equation model.

The results show that both informational and normative social influences have positive effects on FOMO, which in turn exert an influence on compulsive buying. In addition, informational social influence also directly and positively affects compulsive buying.

This study provides a deeper understanding of FOMO and social influence in the process of compulsive buying. It offers a new avenue to analyze the mechanism regarding why compulsive buying occurs in live streaming commerce.