The impact of social shopping feature richness on buying intention: a product perspective

PurposeSocial shopping platforms have flourished by using multiple social shopping features, yet little is known about how the combination of these features affects purchase intention, particularly in terms of the product itself. The purpose of the paper is to draw on the concept of social shopping feature richness, adopting a formative approach on the survey used, and endeavors to reveal the concept's impact on consumers' buying intention from a product perspective.Design/methodology/approachBuilding on mental accounting and signaling theories, a theoretical model is proposed and empirically evaluated with 356 samples collected using a questionnaire survey.FindingsThe results suggest that social shopping feature richness promotes consumers' consumption by providing information signals to satisfy acquisition utility and transaction utility. Specifically, social shopping feature richness enhances perceived product quality, while decreasing negative perceptions regarding price. Moreover, perceived product quality and perceived price significantly influence buying intention through the mechanism of perceived value.Originality/valueThe authors' study highlights the role of the combination of functionally diverse social shopping features on product sales for social shopping platforms.

Health-related fake news during the COVID-19 pandemic: perceived trust and information search

PurposeHealth-related online fake news (HOFN) has become a major social problem. HOFN can lead to the spread of ineffective and even harmful remedies. The study aims to understand Internet users' responses to HOFN during the coronavirus (COVID-19) pandemic using the protective action decision model (PADM).Design/methodology/approachThe authors collected pandemic severity data (regional number of confirmed cases) from government websites of the USA and China (Studies 1 and 2), search behavior from Google and Baidu search engines (Studies 1 and 2) and data regarding trust in two online fake news stories from two national surveys (Studies 2 and 3). All data were analyzed using a multi-level linear model.FindingsThe research detected negative time-lagged relationships between pandemic severity and regional HOFN search behavior by three actual fake news stories from the USA and China (Study 1). Importantly, trust in HOFN served as a mediator in the time-lagged relationship between pandemic severity and search behavior (Study 2). Additionally, the relationship between pandemic severity and trust in HOFN varied according to individuals' perceived control (Study 3).Originality/valueThe authors' results underscore the important role of PADM in understanding Internet users' trust in and search for HOFN. When people trust HOFN, they may seek more information to implement further protective actions. Importantly, it appears that trust in HOFN varies with environmental cues (regional pandemic severity) and with individuals' perceived control, providing insight into developing coping strategies during a pandemic.

Artificial intelligent chatbots as brand promoters: a two-stage structural equation modeling-artificial neural network approach

PurposeThis study investigates the determinants of effective human and artificial intelligence (AI) relationship-building strategies for brands. It explores the antecedents and consequences of consumers' interactant satisfaction with communication and identifies ways to enhance consumer purchase intention via AI chatbot promotion.Design/methodology/approachMicrosoft Xiaoice served as the focal AI chatbot, and 331 valid samples were obtained. A two-stage structural equation modeling-artificial neural network approach was adopted to verify the proposed theoretical model.FindingsRegarding the IQ (intelligence quotient) and EQ (emotional quotient) of AI chatbots, the multi-dimensional social support model helps explain consumers' interactant satisfaction with communication, which facilitates affective attachment and purchase intention. The results also show that chatbots should emphasize emotional and esteem social support more than informational support.Practical implicationsBrands should focus more on AI chatbots' emotional and empathetic responses than functional aspects when designing dialogue content for human–AI interactions. Well-designed AI chatbots can help marketers develop effective brand promotion strategies.Originality/valueThis research enriches the human–AI interaction literature by adopting a multi-dimensional social support theoretical lens that can enhance the interactant satisfaction with communication, affective attachment and purchase intention of AI chatbot users.

Capturing behavioural outcomes through branded applications: the perspective of the investment model

PurposeNumerous companies have launched branded applications to foster consumer–brand relationships. Due to fierce competition among branded apps, the retention rate is quite low. The facilitation of behavioural outcomes through branded apps is a highly relevant research area. This paper investigates the drivers of behavioural outcomes in the context of branded apps from an investment model perspective.Design/methodology/approachThis work examines various branded apps primarily used by consumers in disparate product categories, namely, Target, Walmart, Under Armour, Nike, Pandora, Spotify, Starbucks, Burger King, Disney and Netflix. Four hundred and one valid online questionnaires were obtained and partial least squares structural equation modelling was used for data analysis.FindingsThe results obtained extend the investment model to the context of branded apps and show that app investment size and app satisfaction facilitate brand relationship commitment, successively enhancing app continuance intention, brand purchase intention and app word-of-mouth (WOM) intention. Furthermore, app confidence benefits and self-enhancement benefits facilitate app satisfaction, while app social benefits and special treatment benefits facilitate app investment size.Originality/valueThe present work applies an investment model to various branded apps to show how relationship components facilitate behavioural outcomes. We contribute to the literature by identifying four types of app relational benefits as drivers of relationship components in the context of branded apps.

Impact of media multitasking on executive function in adolescents: behavioral and self-reported evidence from a one-year longitudinal study

PurposeThe longitudinal impact of media multitasking on the development of executive function has been understudied, as most of the existing studies are cross-sectional. This longitudinal study addresses this research gap and uses multiple measures, i.e. behavioral and self-reported, to explore the impact of media multitasking on the executive function of Chinese adolescents.Design/methodology/approachThis study followed 99 Chinese adolescents (Mage = 14.41, SD = 1.10; 42 boys and 57 girls) for one year using both behavioral (2-back, Stroop Color and Number-letter tasks) and self-reported (questionnaire) measures. The adolescents were categorized as either heavy/high media multitaskers (HMMs; 19 boys and 29 girls) or light/low media multitaskers (LMMs; 23 boys and 28 girls). They were tested at baseline, 6 months later and 12 months later.FindingsThe results indicated that the accuracy scores for all cognitive tasks differed with age, but the switch-cost in the shifting task and the self-reported measures of executive function did not. And there were consistent differences between the HMMs and LMMs in the self-reported measures and 2-back accuracy. However, the interaction effect was found only in shifting ability, indicating a decline in the LMMs' self-reported problematic shifting behavior in daily life.Originality/valueThis study used behavioral and self-reported measures to confirm the longitudinal impact of media multitasking on executive function. The impact of media multitasking on executive function is more apparent in daily-life behavior than in cognitive task performance.

The effect of network structure on the purchase of virtual goods on social networking services

PurposeThis paper aims to identify the effect of social structure variables on the purchase of virtual goods. Using field data, it also tests whether their effects on a social networking service are dynamic.Design/methodology/approachTo achieve the research objectives, the authors have applied the random effects panel Tobit model with actual time-series corporate data to explain a link between network structure factors and actual behavior on social networking services.FindingsThe authors have found that various network structure variables such as in-degree, in-closeness centrality, out-closeness centrality and clustering coefficients are significant predictors of virtual item sales; while the constraint is marginally significant, out-degree is not significant. Furthermore, these variables are time-varying, and the dynamic model performs better in a model fit than the static one.Practical implicationsThe findings will help social networking service (SNS) operators realize the importance of understanding network structure variables and personal motivations or the behavior of consumers.Originality/valueThis study provides implications in that it uses various and dynamic network structure variables with panel data.

The influence of information configuration on mobile game download

PurposeThe study aims to show how several factors interact to promote mobile game download: the number of games released by a publisher, the quality of the games released, the popularity of a game's genre, the quality of borrowed intellectual property, the frequency of recommendations, intragenre ranking, consumer rating and review quantity.Design/methodology/approachSignaling theory was used to classify the mobile game information displayed on the Apple App Store into four groups. A conceptual model was proposed to illustrate the complex relationship between the information and download. Based on information on 203 mobile games in the seven days following their release, the model was empirically tested to identify the influence of information configuration on game download by combining fuzzy qualitative comparative analysis (fsQCA) and a fuzzy cognitive map (FCM).FindingsThree solutions were identified for high game download and two for low/medium. The number of previous games released by a publisher, intragenre ranking, consumer rating and review quantity are core conditions that reinforce high game download. The effects of one information type on another and on downloads change as coexisting information types change.Originality/valueThis study enriches existing knowledge about how combinations of multiple types of game information lead to game download and extends previous variance-based research. Combining an FCM with fsQCA can facilitate one’s understanding of the complex causal relationships between game information and download.

To track or not to track: examining perceptions of online tracking for information behavior research

PurposeThis study investigates perceptions of the use of online tracking, a passive data collection method relying on the automated recording of participant actions on desktop and mobile devices, for studying information behavior. It scrutinizes folk theories of tracking, the concerns tracking raises among the potential participants and design mechanisms that can be used to alleviate these concerns.Design/methodology/approachThis study uses focus groups composed of university students (n = 13) to conduct an in-depth investigation of tracking perceptions in the context of information behavior research. Each focus group addresses three thematic blocks: (1) views on online tracking as a research technique, (2) concerns that influence participants' willingness to be tracked and (3) design mechanisms via which tracking-related concerns can be alleviated. To facilitate the discussion, each focus group combines open questions with card-sorting tasks. The results are analyzed using a combination of deductive content analysis and constant comparison analysis, with the main coding categories corresponding to the thematic blocks listed above.FindingsThe study finds that perceptions of tracking are influenced by recent data-related scandals (e.g. Cambridge Analytica), which have amplified negative attitudes toward tracking, which is viewed as a surveillance tool used by corporations and governments. This study also confirms the contextual nature of tracking-related concerns, which vary depending on the activities and content that are tracked. In terms of mechanisms used to address these concerns, this study highlights the importance of transparency-based mechanisms, particularly explanations dealing with the aims and methods of data collection, followed by privacy- and control-based mechanisms.Originality/valueThe study conducts a detailed examination of tracking perceptions and discusses how this research method can be used to increase engagement and empower participants involved in information behavior research.

Musical consumption, self-control and smartphone addiction: a dual-systems theory perspective and evidence from a survey study

PurposeIn the past decade, smartphone adoption has reached almost 100% in industrialized countries, which is predominantly due to advancements in capabilities. Given the increasing number of people who are addicted to the smartphone and the significant growth of people who consume music via the smartphone, the purpose of the study is to explore the underlying mechanisms through which musical consumption affects smartphone addiction.Design/methodology/approachBased on dual-systems theory, a research model was developed to determine the impact of System 1 (emotion related to music) and System 2 (self-control) on smartphone addiction. A partial-least-squares approach was used to test the model with 294 survey participants.FindingsThe empirical data confirmed the research model. Regarding System 1, musical emotion positively influenced smartphone addiction through musical consumption and musical response. Moreover, musical preference significantly affected musical response. Regarding System 2, self-control negatively predicted smartphone addiction.Research limitations/implicationsThe study is limited, as the participants were college students who are not representative of all populations.Originality/valueThe study extends the literature on the dark side of information technology use and complements a research agenda by Gefen and Riedl (2018) on consideration of music in information systems (IS) research.