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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.

The study investigates how the congruence of online deal popularity and star rating influences service quality expectation in online group buying (OGB) websites. It also investigates the role of authenticity perceptions of online cues.

Two experiments are used to assess the effects of congruence between deal popularity and star rating on service quality expectation for service deals in an OGB website.

The findings suggest that a combination of congruently high deal popularity and high star rating has a stronger effect on expected service quality than a combination of congruently low cues. The findings further suggest that expected service quality is greater under the combination of high deal popularity and low star rating than the combination of low deal popularity and high star rating, showing the differences between incongruent cue combinations. The findings also show the moderating effect of consumer authenticity perceptions of cues on the expected service quality.

The novel contribution of the study is to extend cue congruence theory to explain how congruent online information cues and the consumers' authenticity perceptions of the cues influence consumers' judgment of online deals. The contribution is validated empirically in the context of OGB. The findings advance current knowledge concerning how consumers use online information cues.

This study examines how service feedback and physician popularity affect physician demand in the context of virtual healthcare environment. Based on the signaling theory, the critical factor of environment uncertainty (i.e. disease risk) and its impact on physician demand is also investigated. Further, the research on the endogeneity of online reviews in healthcare is also examined in the current study.

A secondary data econometric analysis using 3-wave data sets of 823 physicians obtained from two PRWs (Healthgrades and Vitals) was conducted. The analysis was run using the difference-in-difference method to consider physician and website-specific effects.

The study's findings indicate that physician popularity has a stronger positive effect on physician demand compared with service feedback. Improving popularity leads to a relative increase in the number of appointments, which in turn enhance physician demand. Further, the impact of physician popularity on physician demand is positively mitigated by the disease risk.

The authors' research contributes to a better understanding of the signaling transmission mechanism in the online healthcare environment. Further, the findings provide practical implications for key stakeholders into how an efficient feedback and popularity mechanism can be built to enhance physician service outcomes in order to maximize the financial efficiency of physicians.

The purpose of this paper is to draw on social exchange theory and heuristic–systematic model to examine how peer-to-peer (P2P) lending firms can enhance their customer acquisition by achieving mobile social media popularity.

Content data collected from multiple sources (websites and mobile applications) were employed to validate the research model.

The mobile social media popularity of P2P lending firms positively influences their customer acquisition. Furthermore, the heuristic cues (i.e. source credibility and content freshness) and the systematic cue (i.e. transaction relevance) potentially affect the firms’ mobile social media popularity.

Mobile social media is not only a platform for firms’ image-building but a critical means of acquiring actual customers. The appropriate use of heuristic–systematic cues in a mobile interface is useful for firms to achieve high user popularity despite the challenges derived from the mobile context.

To achieve higher user popularity in the competitive online world, firms should dedicate greater effort in determining the adequate heuristic–systematic cues designed for the interface of their mobile social media account. The effect of popularity can then help the firms acquire more customers.

This study extends the understanding of social exchange in the context of mobile social media accounts and enriches the knowledge on business value of mobile social media popularity. This paper also contributes to the literature by relating heuristic–systematic cues to firms’ mobile social media popularity.

Online reviews are regarded as a source of information for decision-making because of the abundance and ready availability of information. Whereas, the sheer volume of online reviews makes it hard for consumers, especially the older adults who perceive more difficulties in reading reviews and obtaining information compared to younger adults, to locate the useful ones. The main objective of this study is to propose an effective method to locate valuable reviews of mobile phones for older adults. Besides, the authors also want to explore what characteristics of the technology older adults prefer. This will benefit both e-retailers and e-commerce platforms.

After collecting online reviews related to mobile phones designed for older adults from a popular Chinese e-commerce platform (JD Mall), topic modeling, term frequency-inverse document frequency (TF-IDF), and linguistic inquiry and word count (LIWC) methods were applied to extract latent topics and uncover potential dimensions that consumers frequently referred to in their reviews. According to consumers' attitudes towards different popular topics, seven machine learning models were employed to predict the usefulness and popularity of online reviews due to their excellent performance in prediction. To improve the performance, a weighted model based on the two best-performing models was built and evaluated.

Based on the TF-IDF, topic modeling, and LIWC methods, the authors find that older adults are more interested in the exterior, sound, and communication functions of mobile phones. Besides, the weighted model (Random Forest: Decision Tree = 2:1) is the best model for predicting the online review popularity, while random forest performs best in predicting the perceived usefulness of online reviews.

This study’s findings can help e-commerce platforms and merchants identify the needs of the targeted consumers, predict reviews that will get more attention, and provide some early responses to some questions.

The results propose that older adults pay more attention to the mobile phones' exterior, sound, and communication function, guiding future research. Besides, this paper also enriches the current studies related to making predictions based on the information contained in the online reviews.

The purpose of this study is to summarize the findings of consumer factor research and to suggest future lines of inquiry connected to branding outcomes. Consumers are comfortable with social media and accept firms occupying the same digital space. However, some consumers more readily engage with firms online than others. Consumer factor antecedents are numerous and yet not fully explored. Online consumer engagement has also been defined and measured in various ways. The resultant outcomes related to branding also have implications for future consumer engagement. Summarizing the findings of consumer factor research and suggesting future lines of inquiry connected to branding outcomes will enhance the understanding of consumer engagement and branding strategies to maximize marketing return on investment.

The authors review literature examining key constructs and sub-dimensions on how consumer factors impact brand engagement and brand outcomes.

Three major research areas specific to consumer factors were identified: consumer status, consumer disposition, personality trait, intrinsic motivation, extrinsic motivation and cultural dimensions. Brand engagement was explored relative to affective, cognitive and behavioral engagement. Lastly, six brand outcomes were explored: brand status, disposition, attitude, affirmation connection and aversion.

This review contributes to the literature through a deeper understanding of consumer factors that lead to consumer engagement and the resultant branding factors of consumer engagement. The authors offer framework that both identifies future research needs, and insights into how firms may create, grow and enhance consumer–brand engagement.

Given the dearth of comprehensive brand engagement frameworks in the literature, the authors offer insights into how consumer factors serve as antecedents to brand engagement and identify a research agenda for advancing the field.

This study aims to identify the dimensions used by young consumers to evaluate effective online influencers; determine the impact of demographic segmentation – that is, gender, behavioral segmentation and whether young consumers often follow the advice of online influencers to make a purchase – on the evaluative dimensions. The results will inform advertisers regarding the types of online influencers that they should feature to endorse their products to create desirable promotion effects.

This study adopted a multistage method. This study first conducted eight focus groups with 48 participants between 18 and 24 years of age to explore their evaluation of online influencers. This study then conducted a survey with a questionnaire developed from the focus group results. This study used convenience sampling and administered the questionnaire to 475 participants (mean age, 19.5 years).

The results of factor analysis revealed seven dimensions used by young consumers to evaluate online influencers. The most salient dimensions were credibility, appearance and content production techniques. The results of t-testing also show that gender and behavioral segmentation variables had an impact on these evaluative dimensions in the four tested product categories.

This study provides advertisers with a set of criteria to select appropriate online influencers in various advertising settings, such as the promotion of gender-specific products, and in various product categories that target young consumer markets.

To the best of the authors’ knowledge, this is the first study to examine the dimensions used by young consumers to evaluative online influencers in relation to product endorsement.

The purpose of this paper is to examine the impact of word-of-mouth (WOM) types, WOM valence, content types and discussion topics of user posts on online engagement in two channels of a consumption community. The posts are composed by users on the discussion forum and shared to the Facebook channel of the consumption community by the administrators.

The data for this study were obtained from a popular car consumption community in Vietnam. A total of 505 user posts on the discussion forum were manually coded and assigned to WOM types, valence and content characteristics. The online engagement metrics were measured by the number of views and replies on the discussion forum, and the number of likes, comments and shares on Facebook.

The results indicate that the WOM types and valence have a significant impact on online engagement and the popularity of posts on Facebook is associated with the number of views on a discussion forum. The content type and discussion topic partially influence some factors of the online engagement metrics.

The findings are helpful for consumption community administrators to understand and manage their users’ engagement. Moreover, it indirectly supports brands and companies, since the consumption communities also include sub-communities of particular brands and marketers cooperate with consumption communities for their social media marketing strategies.

This research contributes to the literature of online engagement in two aspects. First, this study examines the impact of WOM types and valence. Second, this is the first study investigating the effects of posts by users within an information flow from a discussion forum to Facebook.

This investigation evaluated four sports fan characteristics (fan identification, trust in internet shopping, attitude towards online purchasing, and perceptions of convenience) and two sports website characteristics (perception of product comparison service, and website price advantage) to assess their ability to differentiate licensed sports merchandise purchasers (buyers), and those who just browsed sports websites (browsers). The results made it possible to differentiate buyers and browsers based on 'trust in internet shopping', 'attitude towards online purchasing', 'perceptions of convenience', and 'website price advantage'. Additionally, all six characteristics collectively explained sports merchandise consumers buying versus browsing.

The purpose of this paper is twofold: to identify levels of uptake of performance measurement by small and medium‐sized retail companies selling goods online, and to determine key factors, which could explain any variation in use of performance indicators. The study is designed to explore these issues by this type of retailer as currently understanding is fairly limited.

A quantitative mail questionnaire was used to survey UK retailers selling goods online. The questionnaire examined the uptake of performance measurement in conjunction with the business profile of each of the 252 responding companies.

The results show great variation in levels and extent of uptake of performance measurement by online retailers in the UK. Company profile variables: size and operating format help to account for the variation in the number of indicators measured.

The sample frame has some limitations insofar as the study only focused on small and medium‐sized retailers in the UK selling tangible goods. Future research could be extended to include larger and pan‐European retailers selling both tangible and intangible goods. Furthermore, the data collection was cross‐sectional and, whilst this approach was important at this stage in order to provide a picture of how performance measurement is being applied at a given point in time, a longitudinal study would enable greater analysis of strategic impact of performance measurement.

Currently, retailers' performance measurement activities mainly focus on gathering data using financial and Website functionality indicators. From a strategic planning perspective, this could suggest that retailers are adopting a short‐term pragmatic approach towards retailing online. The implications are that performance measurement is being used as a means to ensure that Internet retailing is not having a detrimental effect on business performance rather than driving longer‐term strategy development.

The principal contributions of this paper are that it has provided insight into the current status of performance measurement amongst UK Internet retailers and has identified a useful checklist of performance indicators which retailers can apply to gain a comprehensive view of business performance online.