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The purpose of this paper is to examine the influence of electronic referral (eReferral) marketing and electronic word-of-mouth (eWOM) on brand image and purchase intention, coupled with the moderating effect of gender in the relationship.

Structural equation modeling was applied to examine the interplay between the proposed variables, using a random sample of 308 respondents in Cyprus.

The empirical results suggest the following: eReferral does influence brand image, and the impact is significant with women only; eWOM influences brand image, and the impact is more significant with women than men; eWOM influences purchase intention, and the impact is the same for both genders; brand image influences purchase intention, and the impact is more significant with women than men.

Marketing managers can benefit from these competitive advantage tools. Brand image, awareness and sales volume can be increased by utilizing eWOM or eReferral, depending on the product and/or service functionality as well as gender.

While there is a substantial research stream on eWOM, to the best of the authors’ knowledge no research has differentiated eReferral from eWOM. This paper provides useful insights regarding the two concepts.

The purpose of this work is to test several incentive strategies for attaining new customers via electronic referrals, or e‐referrals. The paper aims to examine: the roles of both the magnitude of the incentive offered to the sender and the magnitude of the incentive offered to the receiver; and the effect of equity versus inequity of financial incentives for the two parties.

The study consisted of a large‐scale field experiment conducted with 45,000 members of an online mall. The participants were divided into eight conditions in an incomplete two‐factor 4×4 between‐subjects design, where not every combination of incentive magnitudes was utilized and the magnitude of the incentive offered the receiver and sender varied in size such that sometimes rewards were equal, sometimes receivers of the e‐referral had larger rewards, and sometimes senders of the e‐referral s received more. Dependent measures included the number of e‐referrals sent, the number of those e‐referrals that lead to a new customer registering, and the number of new registrants that converted to buyers from completing a purchase.

The results demonstrate that both the magnitude of financial incentives, and the relative magnitude of the incentives for the senders and receivers both influence e‐referral rates. Specifically, it was found that offering higher incentives to senders and receivers led to an increase in referral invitations sent, new member sign‐ups and new buyers. It was also found that the disparity between incentives offered to senders and receivers affected e‐referral rates and that inequity should favor the sender to enhance results.

This paper offers marketers valuable insights as to how different combinations of financial incentives to receivers and senders can affect e‐referral rates. The findings suggest that potential referrers respond not only to referral incentives but also to the disparity between their incentives and the receivers' incentives.

Despite recognizing the importance of eReferral in shaping tourists’ behavioral intentions, researchers have rarely explored its dynamics. In the recent years, interest in the superiority of interactive eReferral over eWOM has burgeoned, thus increasing theoretical and empirical quest, which has generated many inconsistencies. Drawing on social identity, trust transfer and social tie theories, the purpose of this paper is to explore an integrative model that investigates the impact of interactive eReferral on tourists’ engagement, eReferral sharing behavior and intention to visit. Besides the direct influences of interactive eReferral on tourists’ engagement, eReferral sharing behavior and intention to visit, the authors assess the mediating role of tourist engagement on the relationship between these concepts.

Utilizing survey data, variance-based structural equation modeling (VB-SEM) was applied to diagnose the proposed model.

VB-SEM results suggest that interactive eReferral has a positive impact on tourist engagement, eReferral sharing behavior and intention to visit. Tourist engagement mediates the link between interactive eReferral and eReferral sharing behavior, and intention to visit.

By examining the relationship between interactive eReferral, tourists’ engagement, eReferral sharing behavior and intention to visit, the model departs from existing views to shed new light on the interactivity of eReferral. Implications for marketing practices and research are discussed.

Little empirical attention has been paid to the effects of electronic word-of-mouth (eWOM), electronic referral (eReferral), familiarity and cultural distance on behavioral outcomes, especially within the context of educational tourism. Based on the social network theory, this paper aims to explore the effects of eReferral, eWOM, familiarity and cultural distance on enrollment intention.

Survey data (n = 931) were obtained from educational tourists using a judgmental sampling technique. Linear modeling and artificial intelligence (i.e. artificial neural network [ANN]) techniques were used for training and testing the proposed associations.

The results suggest that eReferral, eWOM, familiarity and cultural distance predict intention to enroll both symmetrically (linear modeling) and asymmetrically (ANN). The asymmetric modeling possesses greater predictive validity and relevance.

This study contributes theoretically and methodologically to the management literature by validating the proposed relationships and deploying contemporary methods such as the ANN. Implications for practice and theory are discussed.

是否在线推荐, 在线口碑, 熟悉度, 还有文化距离决定参加意图吗？人工智能科技的应用

很少有研究检测过在线口碑（eWOM）, 在线推荐（eReferral）, 熟悉度, 和文化距离对行为结果的影响, 特别是在教育旅游的领域里。本论文基于社交网络理论探索eReferral, eWOM, 熟悉度, 和文化距离对参加意图的作用。

研究样本数据为931位教育旅游的游客, 通过判断抽样技术。本论文通过线性建模和人工智能（即人工神经网络）技术来培训和检测提出的关系。

研究结果表明, eRefferal, eWOM, 熟悉度, 和文化距离对参与意图起到决定作用, 其中包括对称（线性建模）和非对称地（人工神经网络）方式。非对称建模将增加有效性和相关性的决定度。

本论文通过证实提出的关系和采用现代方法, 比如人工神经网络, 对管理文献做出理论和实践的贡献。本论文还讨论了对实践和理论的启示。

The purpose of this paper is to investigate the distinct reasons and more common reasons that reduce customer satisfaction and are antecedents to customer churn behavior in the telecommunication industry.

The study adopted the netnography approach to investigate churn behavior by utilizing online user-generated content in qualified social media communities.

The investigation revealed that “data speed issue”, “ineffective relationship building”, “service area coverage issues” and “billing issues” are some of the most important attributes that influence a consumers' decision to churn. Further, the churn consequence influencers model summarizes the attributes that contribute to overall dissatisfaction and finally results in churn behavior. The study found out the application of the netnography approach in a quantitatively dominant research area and stands out with its insights from a rich qualitative data.

Proper clarification of customer expectations and pain points can help reduce customer churn. The study will serve as the basis for developing future churn prediction models that will contribute to the informed decision-making process.

Contributing to research on customer churn behavior, the study offers a novel attempt to study customer satisfaction and customer churn behavior jointly. The paper is the first attempt that contributes to the extant literature by adopting the unique qualitative approach to understand the reasons for telecommunication churn behavior in the emerging Indian market. Another contribution of this research is that the paper shifts the focus of the electronic word-of-mouth (eWOM) literature to the telecommunications industry, thus adding another block to ongoing research in eWOM communication.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ OIR-02-2020-0048

Based on climate issues and carbon emissions, this study aims to promote low-carbon consumption and compel consumers to actively shift to energy-saving appliances. In this big data era, online reviews in social and electronic commerce (e-commerce) websites contain valuable product information, which can facilitate firm business strategies and consumer comparison shopping. This study is designed to advance existing research on energy-saving refrigerators by incorporating machine learning models in the analysis of online reviews to provide valuable suggestions to e-commerce platform managers and manufacturers to effectively understand the psychological cognition of consumers.

This study proposes an online e-commerce review mining and management strategy model based on “data acquisition and cleaning, data mining and analysis and strategy formation” through multiple machine learning methods, namely, Bayes networks, support vector machine (SVM), latent Dirichlet allocation (LDA) and importance–performance analysis (IPA), to help managers.

Based on a case study of one of the largest e-commerce platforms in China, this study linguistically analyzes 29,216 online reviews of energy-saving refrigerators. Results indicate that the energy-saving refrigerator features that consumers are generally satisfied with are, in sequential order, logistics, function, price, outlook, after-sales service, brand, quality and space. This study also identifies ten topics with 100 keywords by analyzing 18 different refrigerator models. Finally, based on the IPA, this study allocates different priorities to the features and provides suggestions from the perspective of consumers, the government and manufacturers.

In terms of limitations, future research may focus on the following points. First, the topics identified in this study derive from specific points in time and reviews; thus, the topics may change with the text data. A machine learning-based online review analysis platform could be developed in the future to dynamically improve consumer satisfaction. Moreover, given that consumers' needs may change over time, e-commerce platform types and consumer characteristics, such as user profiles, can be incorporated into the model to effectively analyze trends in consumers' perceived dimensions.

This study fills the gap in previous research in this field, which uses small-sample data for qualitative analysis, while integrating management ideas and proposes an online e-commerce review mining and management strategy model based on machine learning methods. Moreover, this study considers how consumers' emotional and thematic preferences for products affect their purchase decision-making from the perspective of their psychological perception and linguistically analyzes online reviews of energy-saving refrigerators using the proposed mining model. Through the improved IPA model, this study provides optimizing strategies to help e-commerce platform managers and manufacturers.

Companies are interested in engaging consumers in spreading the word about their products or brands. Although more and more studies are analysing word of mouth marketing (WOMM), the topic is still very recent, thus very little is known about how to develop a WOMM campaign effectively. This chapter develops a literature review on WOMM in social media for better understanding on how to manage WOMM.

The studies reviewed have allowed us to identify the main decisions that should be taken when planning a WOMM campaign: the selection of the seed, the type of message and the inclusion of incentives.

We identify the two types of objectives that companies can follow with WOMM: information diffusion or consumers’ persuasion. Depending on the campaign objectives, the strategy to be used in order to be successful is different.

This chapter can be useful to both, marketers, by showing them how to develop a WOMM campaign effectively; and researchers, by showing them the main gaps on WOMM that should be addressed in future studies.

This is one of the first attempts to review the literature and organize knowledge on WOMM. Concepts that have been treated as synonymous by many researchers such as opinion leaders, market mavens, innovative consumers, and hubs are clarified and distinguished one from the other which may help in improving previous knowledge on this field.

The purpose of this paper is to describe the recent efforts of a large publicly funded healthcare organisation in Sydney, Australia to implement integrated care (IC) “at scale and pace” in the messy, real-world context of a District Health Service.

The paper outlines the theoretical and practical considerations used to design and develop a localised IC Strategy informed by the “House of Care” model (NHS England, 2016).

The need for cross-agency partnership, a shared narrative, joint leadership and an IC Strategy underpinned by proven theoretical models model is described.

This paper highlights key factors relating to implementation and evaluation of a local IC Strategy in the real world.

In many healthcare systems, health policy has committed to delivering an integrated model of care to address the increasing burden of disease. The interface between primary and secondary care has been identified as a problem area. This paper aims to undertake a scoping review to gain a deeper understanding of the markers of integration across the primary–secondary interface.

A search was conducted of PubMed, SCOPUS, Cochrane Library and the grey literature for papers published in English using the framework described by Arksey and O'Malley. The search process was guided by the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA).

The initial database search identified 112 articles, which were screened by title and abstract. A total of 26 articles were selected for full-text review, after which nine articles were excluded as they were not relevant to the research question or the full text was not available. In total, 17 studies were included in the review. A range of study designs were identified including a systematic review (n = 3), mixed methods study (n = 5), qualitative (n = 6) and quantitative (n = 3). The included studies documented integration across the primary–secondary interface; integration measurement and factors affecting care coordination.

Many studies examine individual aspects of integration. However, this study is unique as it provides a comprehensive overview of the many perspectives and methodological approaches involved with evaluating integration within the primary–secondary care interface and primary care itself. Further research is required to establish valid reliable tools for measurement and implementation.