Earticle

Distrust of the population in vaccination is one of the key problems of modern healthcare. Therefore, the peculiarities of the spread of anti-vaxxer narratives are a popular subject of sociological research. The largest Russian social network, VK, has several hundred communities that actively published content on the topic of vaccination against COVID-19 during the pandemic. They reflect a sharp polarization of opinion. The self-positioning of these communities makes it possible to divide them into pro-vaxxers, anti-vaxxers and neutrals. Network analysis of these communities showed differences in the behavior of supporters and opponents of vaccination in the digital space. There were significantly more communities against vaccinations. The network of anti-vaxxer communities has a significantly higher degree of density compared to pro-vaxxer communities. The leading communities according to various network criteria are the antixer communities. The results confirm the greater activity, cohesion and propensity for consolidation of anti-vaxxers compared to pro-vaxxers. The reasons are related to the characteristics of people's behavior in risky situations (prospect theory by Daniel Kahneman and Amos Tversky). In situations of health threat, people tend to take risks. Radical anti-vaxxers are seeking to take advantage of this situation. Mass vaccinations are becoming a reflection of broader socio-political tensions.

This study explores implications of different theoretical perspectives for studies of governance contexts in IT outsourcing. Institutional economics views institutions as exchange safeguards. Efficacy of institution-as-safeguard hinges on institutions’ regulative structures to enforce norms. In privately-ordered exchanges, their advantage lies in their capacity for exercising informal sanctions such as reputation- or status-modifying articulations or ostracism and/or authoritative sanctions via control of compensation or career advancement. Thus, institution- as-safeguard implicitly privileges institutions’ regulative structures over its cognitive structures. Do institutions offer governance advantages in the absence of strong regulative structures? If so, how does this occur? These are the questions addressed in this study. The alternative to the institution-as-safeguard paradigm developed to answer the questions is an institution-as-scaffold model, focusing on institutions’ cognitive/normative structures. We examine questions posed in the context of IT outsourcing by 276 Korean firms, contrasting Chaebol (institutionally-embedded) with non-Chaebol exchanges. Findings show that Chaebol exchanges manifested more relational contracting and a higher degree of outsourcing than did non-Chaebol exchanges. This speaks to the salience of institutional embeddedness, despite the institution's hobbled regulative structures. Rather than complementing institutional embeddedness, as the institution-as-safeguard paradigm would expect, we found efficacy of institutional embeddedness diminished with increasing relational contracting. Findings thus supported the institution-as-scaffold perspective advanced.

Online reviews have a significant influence on purchasing decisions. Online reviews typically comprise star ratings and text content, both of which consumers consider when evaluating a product to reduce uncertainty. Previous studies have primarily concentrated on the isolated effects of these factors, assuming a strong correlation between star ratings and text context. However, there is a lack of research on the effect of review inconsistency on consumer perceptions, in which the sentiment conveyed in the text differs from the assigned star rating. By arguing that review inconsistency may provide more nuanced insights for consumers and has the potential to be positive in certain situations, this study explored the impact of review inconsistency on the perceived usefulness of reviews. In particular, we investigate the impact of two different inconsistencies between star ratings and review text, namely, degree and direction inconsistencies, by examining the circumstances under which these inconsistencies may stimulate consumer curiosity and prompt more comprehensive information processing. The analysis of data from 41,258 reviews of 183 products on Amazon.com suggests that review inconsistency can be perceived positively depending on contextual factors such as product awareness and review negativity. This study provides novel insights into consumer information processing and review platform design.

Workplace cyberbullying has become a significant problem in digital workplaces, impacting employee engagement and well-being severely. The study combines qualitative and quantitative data to address this problem and obtain a richer information perspective. The interview results of employees from the qualitative research confirmed that cyberbullying is a widespread phenomenon in the digitalized work environment. Also, participants felt an extensive lack of support from their organizations in dealing with cyberbullying incidences and digitalization- related pressures. The quantitative study with 388 employees found statistically significant relationships between cyberbullying experiences and lower work engagement, as well as a negative impact on well-being. The moderating role of perceived organizational support between cyberbullying and employee engagement and well-being becomes insignificant in the digital work environment. This study's results highlight the consequences of cyberbullying in digitalized work environments and pinpoint an organizational shift that still needs to be present. This study indicates the need for digital-media-specific anti-cyberbullying policies, accompanying awareness programs, as well as psychological support. Future studies might consider intervention programs customized for digitalized work environments and focus on how organizational support can moderate the consequences of cyberbullying among employees.

The current study aims to examine how engaging in online fan communities influences loyalty behavior for a human brand in positive and negative ways through members’ feelings of social well-being and normative community pressure. Structural equation modeling analysis was conducted to test our proposed hypotheses by using data collected from various online fan communities of human brands in South Korea, such as singers, actors, athletes, and politicians. Our study finds that social well-being and normative community pressure, both of which stemmed from fan community engagement, played significant roles in human brand loyalty. More specifically, fan community engagement increases members’ social well-being, which, in turn, enhances members’ loyalty to the respective human brands. On the other hand, fan community engagement also increases the normative community pressure for members, which, in turn, decreases the loyalty for human brands. Our findings contribute to the extant literature by showing how dynamics in fan community engagement influence human brand loyalty, as the previous studies focusing on the relationship between fan communities and human brand loyalty in the literature are scarce.

Advertising on social media is a vital tool for companies looking to grow their clientele, draw in new clients, and raise brand awareness. With features like feeds, stories, reels, and explore pages, Instagram distinguishes out among other networks. The well-liked Instagram Reels feature provides 15–90 second vertical video snippets that loop. Although Instagram Reels have gained popularity as a technique for advertising, little empirical study has been done on how effective they are. The purpose of this study is to investigate the moderating role of influencer credibility on users’ attitudes and adoption of short video commercials, as well as the ways in which short video attributes affect users’ reactions to reel advertising. Additionally, the study looks into how users’ opinions about short video advertisements, their perceptions of their usefulness, and their intention to utilize them relate to one another. Instagram reel users will receive questionnaires via social media platforms, and those who participate will be asked to complete online surveys in order to collect data. It is anticipated that the study will demonstrate how the characteristics of short films improve users’ opinions of advertisements and their assessment of the value of short video advertising. For companies wishing to promote on social media and gain a deeper understanding of user behavior and ad uptake, the findings will provide insightful information.

Popularity based top-N news recommender systems have often been criticized for limitations like monotonicity and popularity amplification. The probabilistic selection of news articles has been found to theoretically address some of the major limitations of top-N recommendation, but its potential impact on reader behavior has not been examined. Based on the variety-seeking nature of consumption, we hypothesize that the probabilistic system should outperform the top-N system across measures of web traffic, user satisfaction, and reader engagement selected using the Balanced Score Card. For evaluation, we conducted a couple of laboratory based experiments. In the first part, 68 participants were randomly assigned to two groups who were shown the same website. Based on the measures, we calculated the sample size for A/B testing. Web traffic and user satisfaction scores were higher for readers who were shown the probabilistic recommendations by 20% and 10%, respectively. Results regarding reader engagement were statistically insignificant. Based on our findings, we conclude that the probabilistic system can be used by media houses as an alternative to the top-N system.

Due to the rise in infectious diseases such as Covid-19, new standards and attributes have emerged to evaluate hotel services, and certain factors (e.g., hygiene) have become crucial. This has led to numerous research endeavors investigating the effect of pandemic on hotel online reviews by emphasizing review elements such as ratings and textual reviews. Previous online review studies related to the Covid-19 pandemic have primarily focused on distinguishing between overall ratings and textual reviews, with limited perspectives on the interplay between these two factors. However, this study investigated the pandemic's impact on consumer review postings by examining multidimensional ratings and textual comments simultaneously, thus identifying the factors that influence the polarity of textual review. Compared to the pre-Covid-19 era, a positive rating for cleanliness led to a more significant positive change in review polarity after Covid-19. This implies that hotel managers need to quickly identify the specific attributes that affect hotel reviews when an unpredictable crisis occurs and invest in improving performance in those areas. The findings from such research not only apply to pandemics but also offer insights for hotel service providers facing crises marked by heightened customer concerns, indicating how they should perceive and respond to online review ratings and comments.

The application of social media for political campaigns is not a recent phenomenon among political marketing scholars. The social media campaigns of Barack Obama, Donald Trump, and Narendra Modi are among the well-studied cases in the political marketing literature. However, the motivations behind social media campaigns for political candidates in developing countries, such as Nepal, have largely been overlooked in the literature. This paper explores the social media engagement behaviors of three electoral candidates, drawing on social media engagement theory. It analyzes 582 Facebook posts from these candidates using a multi-method approach. The findings from content analysis, sentiment analysis, and thematic analysis reveal distinct messaging patterns, varied voter sentiments, and the motivations of political candidates. The motivations for these candidates’ engagement on social media during elections include fostering voter engagement, expressing gratitude for support, and intrinsic motivation. This research contributes unique insights into the social media engagement behaviors of electoral candidates, providing practical guidance for political campaign managers. Such insights can help create impactful content that resonates with voters, ultimately enhancing political communication on social media platforms.

This research delves into the underlying drivers propelling the adoption of Eco-Friendly Smart Home Services (ESHS). In an era of growing environmental concerns, adopting ESHS is motivated by pro-environmental beliefs, concerns, and perceived value, yet requires a comprehensive understanding of these factors. Integrating the Value-Belief-Norm Theory and the Theory of Planned Behaviour, this study explores how knowledge and facilitating conditions moderate ESHS adoption intentions. The research uses Structural Equation Modeling to analyze the responses from the 230 respondents. Additionally, to identify critical factors influencing consumer intention to purchase ESHS, Importance-Performance Map Analysis was used. The findings demonstrate that environmental beliefs and concerns significantly impact purchase intention for ESHS, moderated by knowledge and facilitating conditions. The research’s novelty lies in its comprehensive theoretical framework, offering a deeper insight into ESHS user intentions and advocating for the accelerated adoption of smart home technology.