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This study examines the dynamic relationships of visit behavior in the multiple channels [personal computer (PC) and mobile channels] on online store sales performance.

The empirical data were from an online store for the period between August 14, 2015 and May 15, 2016. The data consisted of consumer visit behavior and online store sales performance. Vector autoregression with an exogenous variables model was adopted to investigate the dynamic relationships.

The empirical results show significant relationships between visit behavior metrics (number of visitors, average number of visits per visitor and average length of each visit) in the two channels and online store sales performance. The number of visitors through the PC and mobile channels strongly and positively affects online store sales performance both in the short term and in the longer term. Moreover, the number of visitors in the PC channel has the strongest influence on sales performance metrics, followed by the number of visitors and the average number of visits in the mobile channel. The PC channel's visit behavior metrics explain a larger proportion of the sales performance variance than that in the mobile channel.

The previous literature on consumer behavior in multichannel marketing mainly focuses on channel selection or migration, and examines the different factors affecting channel choice behavior. Little is known about the impacts of visit behavior in the multiple channels. This study adopts the heuristic-systematic information processing theory to unveil the impacts of visit behavior metrics in the PC and mobile channels on online store sales performance.

The extensive distribution of fake news on the internet (FNI) has significantly affected many lives. Although numerous studies have recently been conducted on this topic, few have helped us to systematically understand the antecedents and consequences of FNI. This study contributes to the understanding of FNI and guides future research.

Drawing on the input–process–output framework, this study reviews 202 relevant articles to examine the extent to which the antecedents and consequences of FNI have been investigated. It proposes a conceptual framework and poses future research questions.

First, it examines the “what”, “why”, “who”, “when”, “where” and “how” of creating FNI. Second, it analyses the spread features of FNI and the factors that affect the spread of FNI. Third, it investigates the consequences of FNI in the political, social, scientific, health, business, media and journalism fields.

The extant reviews on FNI mainly focus on the interventions or detection of FNI, and a few analyse the antecedents and consequences of FNI in specific fields. This study helps readers to synthetically understand the antecedents and consequences of FNI in all fields. This study is among the first to summarise the conceptual framework for FNI research, including the basic relevant theoretical foundations, research methodologies and public datasets.

The objective of this study is to investigate the interaction effect between incentive type (financial and compassionate incentives) and the ethicality of merchant strategy on consumer willingness to post positive reviews, while also examining potential variations in consumer responses based on consumption experience, shopping frequency and social class.

Building upon construal level theory, we hypothesized the moderating influence of the ethicality of merchant strategy and examined the three-way interaction among consumers’ demographic characteristics (i.e. consumption experience, shopping frequency and social class), incentive type and the ethicality of merchant strategy. To empirically test our hypotheses, we conducted four experiments and employed ANOVA for data analysis.

The ethicality of merchant strategies moderates the association between incentive type and consumer willingness to post positive reviews, with compassionate incentives eliciting more pronounced moral judgments toward merchant strategies compared to financial incentives. The moderating effect of the ethicality of merchant strategy on the relationship between incentive type and consumer willingness to post positive reviews is particularly strong among consumers who have favorable consumption experiences, engage in frequent shopping and belong to lower social classes.

This study contributes to the existing literature on online reviews by examining the impact of compassionate incentives on consumer review behaviors, analyzing the ethicality of merchant strategies within the realm of online reviews and investigating variations in consumer responses to merchant strategies regarding consumption experience, shopping frequency and social class.

This paper examines the relationship between supply chain network structures and firm financial performance and the moderating role of international relations. In this study, which is grounded in social capital theory and applies the perspective of systemic risk, the authors theorize the effects of supply chain network structures on firm performance.

The authors extracted data from two Chinese databases and constructed a supply chain network of the firms concerned based on nearly 4,300 supply chain relations between 2009 and 2018. The authors adopted the fixed effects model to investigate the relationship between supply chain network structures and firm financial performance.

The econometrics results indicate that network structures, including the degree, centrality, clustering coefficients and structural holes, are significantly related to firm financial performance. A significant and negative relationship exists between international relations and firm financial performance. The authors also find that international relations strongly weaken the relationship between supply chain network structures and firm financial performance.

This study, which collects secondary data from developing countries (e.g. China) and explores the impacts of supply chain network structures on firm stock performance, contributes to the existing literature and provides practical implications.

This study aims to provide an objective analysis of the state-of-the-art and intellectual development of publications related to event study methodology in business research.

The sample includes 1,219 papers related to event study methodology, covering all business disciplines and spanning 34 years from 1983 to 2016.

Through three stages of primary analysis, namely, initial sample, citation and co-citation analyses, the authors identified the publication trends, supplementary techniques, influential publications and intellectual clusters in the area of event study methodology in business.

The findings serve as a benchmark for the extensive literature related to event study methodology in business and may facilitate the transference of the amassed useful techniques among disciplines and the identification of future research directions.

The current study represents as a pioneering effort to review event study-related publications using bibliometric analysis.

Although there have been considerable discussions on the business value of adopting blockchain in supply chains, it is unclear whether such blockchain-enabled supply chains (BESCs) can help firms mitigate the negative impact resulting from the recent COVID-19 pandemic. This study aims to answer this important question.

The authors conduct an event study to quantify the financial effects of the COVID-19 pandemic and compare the differences in such effects between treatment firms that have adopted BESCs and matched control firms that have not adopted BESCs. The authors also perform a regression analysis to examine how the role of BESCs in mitigating COVID-19's negative impact varies across firms with different levels of supply chain leanness and complexity. The analysis is based on 88 treatment firms and 88 matched control firms, all of which are publicly listed on the US stock markets.

The test results suggest that although both the treatment and control firms are negatively affected by the COVID-19 pandemic, the effect is less negative for the treatment firms compared to the control firms, demonstrating the role of BESCs in mitigating the negative impact caused by the COVID-19 pandemic. Moreover, the mitigating role of BESCs is more pronounced for firms with lean and complex supply chains.

This study is among the first to provide empirical evidence on the mitigating role of BESCs during the COVID-19 pandemic, highlighting the importance of adopting blockchain in supply chains with high uncertainties and disruption risks.

We investigate the joint impacts of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of reviews and attitude toward the product/service reviewed.

We performed three studies to test our research model, presenting participants with scenarios involving product reviews and prior users' helpful and unhelpful votes across experimental settings.

A high helpfulness ratio boosts users’ trust and influences behaviors in both positive and negative reviews. This effect is more pronounced in attribute-based reviews than emotion-based ones. Unlike the ratio effect, helpfulness magnitude significantly impacts only negative attribute-based reviews.

Future research should investigate voting systems in various online contexts, such as Facebook post likes, Twitter microblog thumb-ups and up-votes for article comments on platforms like The New York Times.

Our findings have significant implications for voting system-providers implementing information techniques on third-party review platforms, participatory sites emphasizing user-generated content and online retailers prioritizing product awareness and reputation.

This study addresses an identified need; that is, the helpfulness votes as an additional trust cue and the joint effects of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of customers in reviews and their consequential attitude toward the product/service reviewed.

This study clarifies the integration-related effects of photos and text on consumer information processing and decision-making outcomes.

The authors conducted an experiment by recruiting 162 workers from Amazon Mechanical Turk. These participants were randomly assigned based on a full factorial, between-subject design with four possible conditions (2 [separate vs alternate layout] × 2 [photo-first vs text-first sequence]). The authors conducted a two-way analysis of variance to test the main effects and the interaction effects of layout and sequence on perceived diagnosticity, pleasantness feelings and attitudes toward products or services reviewed through electronic word-of-mouth (e-WOM); the authors also applied Process Models 4 and 8 to explore the mechanism of these effects.

The experimental results reveal that text-first sequence is generally more effective than photo-first sequence in enhancing perceived diagnosticity and attitudes toward products or services. However, when a photo is displayed first, a separate layout is more effective than an alternate layout in enhancing perceived diagnosticity and attitudes. By contrast, regardless of the sequence, an alternate layout is more effective than a separate layout in inducing pleasantness feeling.

Future studies should further explore photo-based e-WOM, including other photo characteristics (e.g. visual quality, quantity and content).

This study provides guidelines for businesses to use photos on social media to achieve strategic goals.

This study addresses an identified need; that is, how the presentation of photo cues (e.g. layout and sequence) influences consumer decisions.

The purpose of this paper is to propose a new approach recommending friends to social networking users who are also using weight loss app in the context of social networks.

Social network has been recognized as an effective way to enhance overweight and obesity interventions in past studies. However, effective measures integrating social network with weight loss are very limited in the healthcare area. To bridge this gap, this study develops a measure for friend recommendation using the data obtained by weight loss apps; designs methods to model weight-gain-related behaviors (WGRB); constructs a novel “behavior network;” and develops two measurements in experiments to examine the proposed approach.

The approach for friend recommendation is based on Friend Recommendation for Health Weight (FRHW) algorithm. By running this algorithm on a real data set, the experiment results show that the algorithm can recommend a friend who has a healthy lifestyle to a target user. The advantages of the proposed mechanism have been well justified via comparisons with popular friend recommenders in past studies.

The conventional methods for friend recommenders in social networks are only concerned with similarities of pairs rather than interactions between people. The system cannot account for the potential influences among people. The method pioneers to model a WGRB as recommendation mechanism that allow recommended friends to simultaneously fulfill two criteria. They are: first, similarity to the target person; and second, ensuring the positive influence toward weight loss. The second criterion is obviously important in practice and thus the approach is valuable to the literature.