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The present research aims to examine selfie-marketing from a consumer behavior perspective. Creating and sharing selfies are gaining popularity among millennials. The authors seek to understand how this popularity relates to classic research on narcissism and self-concept and to determine the effectiveness of selfie-marketing in visual user-generated content.

A mixed methods approach is used across two studies. Study 1’s qualitative exploration uses the grounded theory method by analyzing semi-structured interviews with millennials. The findings produce three research propositions. These propositions are further developed into testable hypotheses in Study 2’s quantitative investigation, featuring analysis of the variance of online survey data collected from millennials.

The findings suggest that narcissism positively relates to millennials’ attitudes toward and intent to participate in selfie-marketing on visual content-sharing apps. Results also demonstrate that millennials seek to use selfies to present their self-concepts differently in various visual content-sharing environments.

The present research is among the first to focus on the importance of self-presentation and narcissism in regard to consumers’ attitudes and behavioral responses toward selfie-marketing. For marketers, this underscores the importance of understanding the unique nature of user-generated visual content on social media.

Online consumer reviews (OCRs) have emerged as a particularly important type of user-generated information about a brand because of their widespread adoption and influence on consumer decision-making. Much of the existing OCR research focuses on quantifiable OCR features such as star ratings and volume. More research that examines the influence of review elements, aside from numeric ratings, such as the verbatim text, particularly in services contexts is needed. The purpose of this research is to investigate the impact of service failures on consumer arousal and emotions.

The authors present three behavioral experiments that manipulate service failure and linguistic elements of OCRs by using galvanic skin response, survey measures and automated facial expression analysis.

Negative OCRs lead to the greatest levels of arousal when consumers read OCRs. Service failure severity impacts anger, and referential cohesion, an observable property of text that helps a reader better understand ideas in the text, negatively moderates the relationship between service failure severity and anger.

The authors are among the first to empirically test the effect of emotional contagion in a user-generated content context, demonstrating that it can occur when consumers read such content, even if they did not experience the events being described. The research uses a self-report and physiological measures to assess consumer perceptions, arousal and emotions related to service failures, increasing the robustness of the literature. These findings contribute to the marketing literature on OCRs in service failures, physiological measures of consumers’ emotions, the negativity bias and emotional contagion in a user-generated content context.

Artificially intelligent (AI) assistant-enabled smart speaker not only can provide assistance by navigating the massive amount of product and brand information on the internet but also can facilitate two-way conversations with individuals, thus resembling a human interaction. Although smart speakers have substantial implications for practitioners, the knowledge of the underlying psychological factors that drive continuance usage remains limited. Drawing on social response theory and the technology acceptance model, this study aims to elucidate the adoption process of smart speakers.

A field survey of 391 smart speaker users were obtained. Partial least squares structural equation modeling was used to analyze the data.

Media richness (social cues) and parasocial interactions (social role) are key determinants affecting the establishment of trust, perceived usefulness and perceived ease of use, which, in turn, affect attitude, continuance usage intentions and online purchase intentions through AI assistants.

AI assistant-enabled smart speakers are revolutionizing how people interact with smart products. Studies of smart speakers have mainly focused on functional or technical perspectives. This study is the first to propose a comprehensive model from both functional and social perspectives of continuance usage intention of the smart speaker and online purchase intentions through AI assistants.

In this paper the authors seek to compare lay (consumer) and professional (physician) discourse structures in answers to diabetes‐related questions in a public consumer health information website.

Ten consumer and ten physician question threads were aligned. They generated 26 consumer and ten physician answers, constituting a total dataset of 717 discourse units (in sentences or sentence fragments). The authors depart from previous LIS health information behaviour research by utilizing a computational linguistics‐based theoretical framework of rhetorical structure theory, which enables research at the pragmatics level of linguistics in terms of the goals and effects of human communication.

The authors reveal differences in discourse organization by identifying prevalent rhetorical relations in each type of discourse. Consumer answers included predominately (66 per cent) presentational rhetorical structure relations, those intended to motivate or otherwise help a user do something (e.g. motivation, concession, and enablement). Physician answers included mainly subject matter relations (64 per cent), intended to inform, or simply transfer information to a user (e.g. elaboration, condition, and interpretation).

The findings suggest different communicative goals expressed in lay and professional health information sharing. Consumers appear to be more motivating, or activating, and more polite (linguistically) than physicians in how they share information with consumers online in similar topics in diabetes management. The authors consider whether one source of information encourages adherence to healthy behaviour more effectively than another.

Analysing discourse structure – using rhetorical structure theory – is a novel and promising approach in information behaviour research, and one that traverses the lexico‐semantic level of linguistic analysis towards pragmatics of language use.

The association between income distribution and measures of health has been well established such that societies with smaller income differences between rich and poor people have increased longevity (Wilkinson, 1996). While more egalitarian societies tend to have better health, in most developed societies people lower down the social scale have death rates two to four times higher than those nearer the top. Inequities in income distribution and the consequent disparities in health status are particularly problematic for many women, including single mothers, older women, and women of colour. The feminization of poverty is the rapidly increasing proportion of women in the adult poverty population (Doyal, 1995; Fraser, 1987).

Multicommunicating, the practice of using technology to carry on multiple near-simultaneous conversations, has been studied for almost two decades. This practice has new meaning today as more people carry a mobile device with them, remote working is prominent, and teams are looking for ways to be more productive. This chapter establishes why multicommunicating is an important communication concept that can help scholars interested in teams. After distinguishing multicommunicating from related concepts, such as multitasking, this chapter reviews key findings from literature and highlights the conundrum around whether this is a productive, acceptable practice or one that is rude and increases inefficiency. In conclusion, the proposed research agenda invites studies of multicommunicating in contexts where actual responses to the practice can be observed. Additionally, there are growing opportunities to include mobile communication and human–technology interactions in the multicommunicating mix.

Little research has focused on the quality and availability of interactive online support services retrieved through search engines. The purpose of this paper is twofold; first, to review and assess the availability and accessibility of interactive online support available to individuals in suicidal crisis. Second, to field test a new tool developed specifically to evaluate both the quality of online information and the quality of interactive support.

A collection of six terms relating to suicidal distress were generated and inputted across three major search engines (Google, Yahoo and Ask). Following initial exclusions, the remaining web sites were analysed using the SPAT (Site, Publisher, Audience and Timeliness) tool and recently developed COSAT (Crisis and Online Support Appraisal Tool) tool.

The quality of web sites retrieved was variable, with only 1.9 per cent deemed as high-quality interactive support resources. Google had the greatest precision of searching, but ease of access through search engines was generally limited. No significant difference was found in the quality of web sites located on pages 1 or 2 of search engine results. Overall, community and voluntary sector web sites averaged higher quality and interactive support rating's compared to publicly funded web sites.

The newly developed COSAT tool may provide a positive first step towards a standardised measure of online quality and interactive support, although further testing and validation is required with a larger sample size.

To the authors knowledge little research has focused on the quality and availability of interactive online support services retrieved through search engines.

The purpose of this paper is to investigate health care consumers’ diabetes term usage patterns based on Yahoo!Answers social question and answers (Q&A) forum, identified characteristics and relationships among terms within three pairs of related categories identified from the Q&A log, and revealed users’ diabetes term usage patterns.

The Q&A analysis method allowed first-hand investigation of massive data from health care consumers. Visual term clustering analysis across categories was conducted using a multi-dimensional scaling (MDS) visualization method which provides an intuitive and interactive way to explore and discover term association patterns in a visual environment. Closely related categories were identified and corresponding visual term clustering analyses between categories (Sign & Symptom and Organ & Body Part; Diagnosis and Test; and Diagnosis and Medication) as well at the term level were analyzed.

The findings show that there are close relationships between terms in two related categories. Related terms were grouped and patterns were revealed. All the stress values of the MDS analyses fall below 0.10 and RSQ for each of the combined categories is over 0.90 which indicate the investigated terms were well clustered in the visual analyses.

The study provides a unique research methodology for similar consumer health research studies. The results of this study offer insight into consumer health term use behavior, and enrich existing thesauri and subject heading lists, enhance diabetes-related web sites or portals, and improve effectiveness of internal search engines.