Search

As many services convert to digital based on human-machine communication technology, older adults face considerable challenges. With the goal to identify ways to design digital services that are easier for older adults to use, this paper uses the strategy of making self-ordering kiosks more similar to the original version (i.e., paper menu) focusing on three familiarity design approaches: representation, manipulation, and organization. A 2 (skeuomorphic vs. flat design) x 2 (hierarchical vs. linear navigation structure) between-subject design experiment was conducted with individuals aged over 65 years (N = 60). Participants perceived that the skeuomorphic design was easier to use compared to the flat design, and the linear navigation structure increased perceived self-efficacy, usefulness, and intention to use compared to the hierarchical navigation structure. Participants also completed the tasks more quickly in the skeuomorphic design (vs. flat design) and linear navigation structure (vs. hierarchical structure) conditions. Interaction effects suggest that the task completion time was further reduced when skeuomorphic design was used with a linear navigation structure. Furthermore, fewer people requested assistance when they used a linear navigation structure. Serial multiple mediation results showed that the influence of linear navigation structure on intention to use was mediated by perceived self-efficacy and usefulness. • Skeuomorphic design offers better user experience for seniors than the flat one. • Linear navigation structure offers better user experience for seniors than the hierarchical one. • Combining skeuomorphism and linear structure decreases the task completion time. • The effect of linear navigation structure on intention to use is mediated by self-efficacy and perceived usefulness. [ABSTRACT FROM AUTHOR]

The increasing usage of social media networks has raised concerns about the growing frequency of cyberbullying incidents. The definition of cyberbullying lacks universal consensus, yet according to several authors, cyberbullying is characterized by aggressive, repetitive, and intentional communication among peers. However, existing cyberbullying detection datasets often focus solely on classifying texts as aggressive or non-aggressive, neglecting the other cyberbullying aspects, thus hindering research progress. This paper proposes a framework for designing a new dataset incorporating all four aspects of cyberbullying to address this gap. The text messages are sourced from a real dataset, while the users' data is generated synthetically. The resulting dataset contains messages exchanged randomly among different pairs of users, thus inculcating repetition. Additionally, the degree of peerness, defined and calculated to measure the likelihood of two users being peers, is used. The intent of harm is quantified as a numeric value using the ratios of aggression and repetition. As a result, the proposed dataset encompasses all four aspects of cyberbullying by providing repeated aggressive messages among users along with quantitative values of the degree of peerness and intent to harm. The proposed dataset is adaptable, with adjustable threshold values for peerness, repetition, and intent to harm, offering flexibility for various applications. The paper concludes by presenting the results of some baseline machine-learning methods on the proposed dataset. • Generation of a semi-synthetic dataset for automatic cyberbullying detection. • The dataset includes all aspects of cyberbullying: aggression, repetition, intent to harm, and occurrence among peers. • Presentation of baseline results on the proposed dataset. [ABSTRACT FROM AUTHOR]

The buyer-seller relationship in live streaming commerce is crucial especially in service failure situations, yet it has been underexplored. In this paper, we reconceptualized the relationship between consumers and sellers in live streaming commerce as "parasocial guanxi", which consists of ganqing (emotional attachment), xinren (trust) and reciprocal value. The effects of parasocial guanxi on consumer dissatisfaction and complaint intention in service failure situations were further investigated based on the expectation confirmation theory. Our study involved 425 valid questionnaires and employed the partial least squares structural equation method (PLS-SEM). The findings are mixed: on one side, parasocial guanxi acts as a buffer, mitigating dissatisfaction and complaint intention in the face of product or service problems and reducing the impact of disconfirmation on consumer dissatisfaction. On the other side, it may also increase the likelihood of dissatisfied consumers complaining. Furthermore, the buffering effect weakens as consumers make more frequent purchases. The findings have important theoretical and practical implications for understanding the buyer-seller relationship in live streaming commerce. • This paper reconceptualized the buyer-seller relationship in live streaming commerce as "parasocial guanxi". • The effects of parasocial guanxi in service failure situations were investigated. • Parasocial guanxi has a buffering effect in alleviating consumers' dissatisfaction and complaint intention. • Meanwhile, parasocial guanxi can increase the likelihood of dissatisfied consumers to complain. • The effects of parasocial guanxi vary across different demographic groups. [ABSTRACT FROM AUTHOR]

Most prior work on online reviews assumes that the value of reviews for consumers lies only in providing information about the product or the consumer's experience with the product. Yet, consumers also post and interact with pseudo-reviews, defined as reviews that describe exaggerated product experiences while trying to be entertaining. To address the nature and consequences of pseudo-reviews, this study develops a framework for understanding their value and how they affect consumer decision-making. First, we define how pseudo-reviews differ from other types of reviews. Then, we empirically examine how pseudo-reviews moderate the relationship between online review valence (how positive or negative the review is) and purchase intention. Finally, using a dual-processing theoretical lens, we examine how pseudo-reviews affect consumer decision-making through systematic and affective processing. We test our model through two experiments. The first study finds that pseudo-reviews reduce the impact of review valence on purchase intention when compared to genuine reviews. The second study shows that pseudo-reviews affect uncertainty and amusement, and these, in turn, affect purchase intention. We discuss the implications of pseudo-reviews for theory and practice. • Previous studies on online reviews often ignore the amusement value of online reviews. • The paper focuses on pseudo-reviews and develops a framework to understand their influence on consumer decisions. • For positive reviews, pseudo-reviews decrease the positive effect of review valence on purchase intention. • Pseudo-reviews affect consumer decisions by increasing both uncertainty and amusement. [ABSTRACT FROM AUTHOR]