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This study explores the link between additional reviews, credibility, and consumers’ online purchasing behavior.

We employ a 2 × 2 between-subjects design to measure subjects’ purchasing behavior with versus without additional reviews and with important versus non-important attributes. A total of 529 valid questionnaires are collected from university students across 30 Chinese provinces.

The addition of negative reviews to a positive initial review enhances consumers’ perceived credibility of the reviewer and the overall review content. This effect is positively moderated by the attribute importance in additional reviews. Moreover, we find that as the time interval increases, consumers’ perceived credibility gradually increases but eventually decreases after reaching a certain threshold. In addition, the attribute importance in additional reviews negatively moderates the impact of perceived credibility on consumer purchasing behavior.

Existing studies on first and subsequent reviews mainly focus on the difference in perceived usefulness between the two. They do not examine how additional reviews affect potential customers’ perceived credibility and their purchase decision-making. This study bridges the gap between the word-of-mouth literature and marketing practices.

Despite the digital penetration in the larger consumer market, the adoption of e-pharmacy services is reported to be very low in emerging economies like India. In this context, the purpose of the current study is to examine the influence of consumers’ risk perception on their intention to purchase medicines/pharmaceuticals through online pharmacies. Furthermore, the study seeks to understand to what extent the perceived usefulness of online pharmacy mediates the relationship between different dimensions of perceived risk and purchase intention.

The study was conducted among a sample of 800 consumers in India who are familiar with online e-commerce. To ensure the homogeneity of the sample and hence the generalizations of results, inclusion criteria were set as not to include respondents who have made a prior purchase through e-pharmacy services. Self-reporting questionnaires were administered among the respondents, who were selected through a purposive and convenience sampling method. Measurement modeling and path analysis were done using IBM SPSS 23.0 and AMOS 24.0 to test the hypotheses and draw inferences.

Results revealed that consumers’ risk perceptions, such as financial, product, source and privacy risks, had a significant direct and indirect effect on their intention to purchase medicines through online pharmacies. India is the major universal provider of generic medicines. The insights gained from this study can help policymakers, corporates, consumers, distributors, retailers and marketing managers to frame effective strategies for improved usage of online platforms for procuring medications.

This study is pioneering in conceptualizing and testing a theoretical model linking consumers’ risk perceptions, perceived usefulness and intention to purchase through online pharmacies, particularly in the context of an emerging economy like India. Implications regarding facilitating and nurturing a conducive platform for online purchasing medicines and its outcomes are elaborated, thus striving to fill a gap in the existing literature. By examining the proposed framework through the lens of the technology acceptance model and theory of risk perception, this study seeks to add to the emergent literature on online pharmacies, especially in emerging economies with huge market potential.

Free knowledge sharing in the online health community has been widely documented. However, whether free knowledge sharing can help physicians accumulate popularity and further the accumulated popularity can help physicians attract patients remain unclear. To unveil these gaps, this study aims to examine how physicians' popularity are affected by their free knowledge sharing, how the relationship between free knowledge sharing and popularity is moderated by professional capital, and how the popularity finally impacts patients' attraction.

The authors collect a panel dataset from Hepatitis B within an online health community platform with 10,888 observations from April 2020 to August 2020. The authors develop a model that integrates free knowledge sharing, popularity, professional capital, and patients' attraction. The hierarchical regression model is used to for examining the impact of free knowledge sharing on physicians' popularity and further investigating the impact of popularity on patients' attraction.

The authors find that the quantity of articles acted as the heuristic cue and the quality of articles acted as the systematic cue have positive effect on physicians' popularity, and this effect is strengthened by physicians' professional capital. Furthermore, physicians' popularity positively influences their patients' attraction.

This study reveals the aggregation of physicians' popularity and patients' attraction within online health communities and provides practical implications for managers in online health communities.

This study draws on social influence and social comparison theories to investigate the effect of social media influencers on intention to visit with the mediating role of upward social comparison. It studies the reasons underlying people's intention to visit a destination from an emotional perspective.

PLS-SEM models were applied to a total of 527 responses.

This study provides empirical evidence supporting the Source Credibility Model's elements within the context of influencer marketing and travel intentions. Furthermore, it expands the current knowledge of upward social comparison emotions by reporting that upward contrastive emotions would partially mediate the relationship between expertise and intention to visit, and that upward assimilative emotions would fully mediate the relationship between attractiveness and intention to visit while partially mediating the relationship between trustworthiness and expertise and intention to visit.

The article adds new insights to tourism marketing as well as helps both destination marketers and travel influencers. For marketers, it is advised to collaborate with credible influencers known for expertise and trustworthiness, leveraging their perspectives to rebuild travel confidence and reassure tourists about safety measures. Travel influencers are recommended to convey their intrinsic passion and enthusiasm through their posts to create an inspiring connection with the audiences.

This paper is the first to address the relationship between travel influencers and intention to visit with the mediation role of both positive and negative emotions.

While founder characteristics have been studied extensively as a factor in attracting employees, organizational attributes of startups have received little attention. To fill the void, this study aims to examine organizational attributes of startups to attract employees.

This research collected 8,817 online employer reviews of 117 startups from Glassdoor.com. This research conducted two studies. In Study 1, a topic modeling approach was applied to identify startup attributes to attract employees having actual employer experience and to examine the importance and relationship of the attributes, drawing the person–organization fit theory. Study 2 used logistic regression analysis to explore the effect of identified attributes on employer attractiveness based on the signaling theory.

Study 1 found six attributes: high-quality coworkers, entrepreneurial culture, development, company outlook, physical office and stereotypical startup perks. This study also found high-quality coworkers, entrepreneurial culture and development are not only related to each other but also more critical attributes than other attributes. The core value of the three attributes can be conceptualized as “learning opportunity.” Study 2 found that employees attracted to “learning opportunity” are more likely to recommend their employers than instrumental attributes, including physical office and stereotypical startup perks.

This research elaborates on employer attributes to attract employees in the context of startup based on the real voices of employees having actual employer experience. Furthermore, this research extends the understanding of employer attributes contributing to employer attractiveness by combining qualitative review data with quantitative rating data.

Compared to traditional (domestic) e-commerce consumers, cross-border electronic commerce (CBEC) consumers may face greater information asymmetry in the CBEC purchase process. Given this background, however, the literature has paid limited attention to the informational antecedents that influence consumers' perceptions of transaction costs and their CBEC purchase intentions. To fill this gap, this study integrates the elaboration likelihood model (ELM) and transaction cost theory (TCT) to develop a model for exploring how product (website informativeness, product diagnosticity and website interactivity as the central route) and external (country brand, website policy and vendor reputation as the peripheral route) informational antecedents affect consumers’ evaluations of transaction costs in terms of uncertainty and asset specificity and their CBEC purchase intentions.

This study employs a survey approach to validate the model with 766 Generation Z CBEC consumers based on judgment sampling. The partial least squares (PLS) technique is adopted for data analysis.

The results show that all the proposed central and peripheral informational antecedents reduce consumers’ perceptions of uncertainty and asset specificity, which in turn negatively influences their CBEC purchase intentions.

Through this investigation, this study increases our understanding of how product and external informational antecedents affect consumers’ evaluations of transaction costs, which subsequently determine their CBEC purchase decisions. This study offers theoretical contributions to existing CBEC research and has practical implications for CBEC organizations and managers.

The digital marketing landscape is rapidly evolving, but the integration of visual content still heavily depends on human expertise. Driven by the quest for innovative marketing strategies that resonate with family-oriented consumers, this study seeks to bridge this gap by applying machine learning to analyze visual content in the maternity and baby care product sector.

This study incorporates a range of machine learning techniques – including open science framework feature detection, panoptic segmentation, customized instance segmentation, and face detection calculation methods – to analyze and predict the appeal of images, thereby enhancing user engagement and parent-child intimacy.

The exploration of various ML models, such as DT, LightGBM, RIPPER algorithm, and CNNs, has offered a comparative analysis that addresses a methodological gap in the existing literature, which frequently depends on isolated model evaluations. According to our quadrant analysis with respect to engagement rate and parent-child intimacy, the selection of a model for real-world applications depends on balancing performance and interpretability.

The proposed system offers a series of actionable recommendations designed to enhance customer engagement and foster brand loyalty. This study contributes to image design in maternity and baby care marketing and provides analytical insights for recommendation systems.

Self-presentation is an important aspect of influencer marketing. Drawing upon self-presentation theory and source credibility theory, this study aimed to unravel how the self-presentation strategies of a layperson, opinion leadership and micro-celebrity influence source credibility (i.e. trustworthiness, expertise, physical attractiveness and social attractiveness) and how source credibility, in turn, affects brand responses.

An online experiment among female participants (N = 229) was conducted. Participants were shown a sponsored blog in which the influencer presented herself as either a layperson, an opinion leader or a micro-celebrity.

The study demonstrated that the presentation strategy of a layperson was more persuasive than a micro-celebrity presentation because of higher levels of (1) trust and (2) social attractiveness. In addition, opinion leaders were perceived as having more expertise than laypeople and, therefore, positively enhanced brand responses.

The current findings provide relevant insights into the theoretical mechanisms (i.e. expertise, trustworthiness and social attractiveness) that explain the effects of self-presentation strategies on brand responses.

Our findings imply that credibility perceptions determine the persuasiveness of the SMI. This study showed that layperson and opinion leadership self-presentation strategies are relatively more persuasive.

This study is the first to show that influencers’ self-presentation strategies determine how people respond to the brands that influencers promote. In addition, we show that these effects are explained by the influencers’ trust, social attractiveness and expertise.

This research aimed to raise awareness about the need for safety measures and features of online food delivery applications (OFDAs) to build electronic trust (e-trust) with augmented purchase intention among customers. Moreover, this study explores the attributes of electronic commerce (e-commerce) and how e-trust influences the purchasing intention of consumers while ordering food through OFDAs including fear of contagious diseases. Determinants of e-commerce in the digital era profoundly impact the performance of enterprises.

Data from 493 food consumers collected from Federal Capital Territory (FCT) Pakistan, who were regular users of OFDAs. To scrutinize the dataset, confirmatory factor analysis (CFA) was conducted to assess the construct validity in this research study. Structural equation modeling (SEM), which is facilitated by Smart-PLS, was employed to examine the direct, moderation and mediation effects of the proposed model.

Results revealed the positive and significant impact of the e-trust on the purchase intention. Additionally, e-trust acted as a mediating factor in the connection between electronic security (e-security), electronic privacy (e-privacy), usability, electronic payment (e-payment), electronic innovativeness (e-innovativeness) and the buyer's purchase intention. Furthermore, the fear of contagious viruses negatively moderated the e-trust and purchase intention that weakened buying behavior.

This research is primarily centered on enhancing the comprehension regarding safety orientation within the context of an evolving restaurant industry. The findings of this study hold substantial contributions for academics, web developers, application designers, OFDAs, restaurants and other businesses since they indicate the attractiveness of OFDAs in generating feelings of pleasure and boosting users' intentions to keep using the application.

The purpose of this study is to empirically examine the relationships between barrier-breakers and customers’ intention to fully adopt digital payment methods (DPMs).

Survey data were analyzed using statistical methods focusing on hypothesis testing with an ordinal regression model and moderation analysis using the PROCESS macro extension. Participants were divided into two groups of customers in Sweden: adopters-accepters, i.e. young bank customers and adopters-resisters, i.e. members of a formally organized group opposed to a cashless society.

The findings revealed that only the credibility barrier-breaker could increase the adopters-accepters’ intention to fully adopt DPMs. Credibility also seemed to be an important barrier-breaker for the adopters-resisters, as were perceived usefulness and social influence. Additional analyses showed that the impersonalization barrier reduces the impact of the barrier-breakers on DPM adoption.

Retail banks and merchants can use these results as a guide to what barrier-breakers might affect various customers’ intention to fully adopt DPMs, and to act accordingly. The impersonalization barrier also merits attention when creating an emotional connection to customers who use DPMs.

This study provides empirically based knowledge of the influence of barrier-breakers on the intention of customers, categorized as adopters-accepters and adopters-resisters, to fully adopt DPMs, and highlights the importance of maintaining a human touch in the post-COVID-19 digital era.