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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.

Policy leadership infiltrates the lives of citizens everywhere. Though this type of leadership is implicit and ubiquitous, a theoretically-based model specifically intended for policy leaders is not readily available in academic literature. This article serves to address this gap by proposing a conceptual model of the policy leadership framework. The model expounds upon previous literature and identifies 16 areas vital to the policy process. Implications of the model relate to equipping leadership educators in the classroom and in the community with enhanced policy leadership research and curriculum.

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.

The need for individuals capable of leading change has become pronounced based on the changes occurring within the higher education system. The purpose of this study was to examine if participation in the LEAD21 leadership development program, a national leadership program for faculty emerging as leaders in the land-grant university system, changed participant levels of change leadership. The longitudinal analysis included comparisons across members of three classes in the LEAD21 program, as well as the aggregated data from all three years. Results indicated overall level of change leadership rose by an average of 28.8%. Additionally, the study established benchmarks for pre-program and post-program levels of change leadership. Leadership educators can use the results to inform future leadership education initiatives. Furthermore, the study presents a Leading Change Scale that may be appropriate for future leadership program evaluations. Ongoing evaluations of leadership programs are encouraged.

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.

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.

This paper aims to establish and empirically investigate a research model examining the effect of four dimensions of the technology readiness index – optimism, innovativeness, discomfort and insecurity – on customer engagement that further influences purchase intention in the context of online shopping through artificial intelligence voice assistants (AI VAs).

Data were collected in India from 429 customers in a self-administered online survey. Data analysis uses the structural equation modelling technique.

Technology readiness dimensions, e.g. optimism, innovativeness, discomfort and insecurity, are critical factors driving customer engagement. Customer engagement further results in purchase intention in online shopping through AI VAs.

This study adds to the literature by understanding how customers’ technology readiness levels drive engagement and purchase intention. However, this study includes customer engagement as a unidimensional construct. Further research can consist of customer engagement as a multidimensional construct.

The findings offer guidelines for e-retailers to enhance customer engagement that matches their personality traits, thereby strengthening their purchase intention through AI VAs.

The research contributes to the literature by empirically investigating a research model, revealing optimism, innovativeness, discomfort and insecurity as crucial parameters for customer engagement and purchase intention.

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.

The purpose of this study is to identify, analyze and explain the ethical implications that can result from the datafication of service.

This study uses a midrange theorizing approach to integrate currently disconnected perspectives on technology-enabled service, data-driven business models, data ethics and business ethics to introduce a novel analytical framework centered on data-driven business models as the general metatheoretical unit of analysis. The authors then contextualize the framework using data-intensive insurance services.

The resulting midrange theory offers new insights into how using machine learning, AI and big data sets can lead to unethical implications. Centered around 13 ethical challenges, this work outlines how data-driven business models redefine the value network, alter the roles of individual actors as cocreators of value, lead to the emergence of new data-driven value propositions, as well as novel revenue and cost models.

Future research based on the framework can help guide practitioners to implement and use advanced analytics more effectively and ethically.

At a time when future technological developments related to AI, machine learning or other forms of advanced data analytics are unpredictable, this study instigates a critical and timely discourse within the service research community about the ethical implications that can arise from the datafication of service by introducing much-needed theory and terminology.