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This study attempts to investigate how electronic Word-of-Mouth (eWOM), consisting of (1) opinion seeking, (2) opinion giving, and (3) opinion passing, influences consumers’ purchasing intentions for tourism services on Social Networking Sites (SNSs). Two hundred and seventy three American college students participate in a self-administered survey concerning their use of SNSs and ways of making online recommendations. Based on four hierarchical regression analyses, this study finds that both opinion seeking and opinion passing significantly influence respondents’ purchasing intentions. Additionally, time spent on SNS use reveals a positive relationship with opinion seeking and opinion passing. The conclusion of the present study highlights the eWOM as a cost-effective communication tool for tourism marketing and renders practical and theoretical implications along with suggestions for future research.

Interest in the Electronic Word-of-Mouth (eWOM) in connection with tourism is constantly growing not only among consumers but also among theoreticians. Therefore, the objective of this chapter is to provide an overview of studies that focus on eWOM in the tourism sector using the snowball method. The article is based on a review of the literature of 60 studies that focus not only on consumer behavior in tourism and the impact of eWOM on tourism supply but also on the impact of hotel managers' responses to other consumer behavior and tourism companies. The results of the studies show that eWOM has a significant impact not only on consumer behavior but also on tourism supply. Manager responses can also strongly affect other consumer behavior in decision-making. When eWOM is distributed, consumers are influenced by their emotions, motives, and also by the websites to which they have decided to contribute. The chapter proposes further research areas for different authors.

This chapter examines how information and communication technology (ICT) initiatives affect customers’ everyday routines with an emphasis on how electronic word of mouth (eWOM) affects their purchasing decisions and determines if eWOM might serve as a useful trust factor when making purchasing decisions. This chapter is based on both primary and secondary data and examines how eWOM affects customers’ buying decisions in this era of increasing social media platform usage. One hundred individuals from various regions of Karachi provided the primary data, collected through an online survey. Secondary data are also employed, such as details from business websites, scientific papers, and other related publications of businesses. In Karachi’s developing digital market, it was discovered that eWOM via social media used to have a substantial impact on consumers’ shopping habits. The effectiveness of social media content depends greatly on how appropriate it is for the intended audience. Social media marketing doesn’t quite simply aim to improve consumers’ impressions or directly advertise things. It also entails maintaining and fostering relationships between businesses and prospective customers. According to the research, consumers’ recommendations and ratings of goods and services made on social media, whether through eWOM or another channel, influenced their decisions to buy. Customers consider social media to be trustworthy when making decisions about what to buy. Customers are currently adopting social media as opposed to more conventional means to learn about new products. Most customers believe that eWOM from social media greatly affected their shopping choices, according to the results of the study.

Electronic word of mouth (eWOM) is a digital marketing method that has been considered by some companies as an effective and efficient approach to enhance social learning and the environment for the customers. A social media user could benefit from gaining information from other users to aid their decision-making process. Instagram is an example of a social media platform that could be utilized for the application of eWOM. It could serve as a source of quality, credible and detailed information, and a channel to increase customer interactions and trust. This study aims to determine the effects of eWOM information generated through Instagram on patients’ intention to join the in vitro fertilization (IVF) programs. By adopting the information acceptance model (IACM) theory, several parameters were evaluated: information quality, credibility, usefulness, adoption, attitude toward information, and purchase intention. The structural equation modeling (SEM) was used to analyze as many as 200 respondents of Morula IVF Jakarta and were active Instagram users. The results showed that the adoption of information and attitude toward information had considerably influenced patients’ intentions to join the IVF programs. Such circumstances might have occurred as a result of the increase in information exchange about IVF, through the discussions and sharing of experiences by patients on Instagram. Furthermore, information usefulness was demonstrated to affect information adoption and was influenced by the credibility of information and attitudes toward information. Nonetheless, one variable which did not display any effects on the usefulness of information was the quality of information. In summary, the characteristics of eWOM information that were conveyed on Instagram could affect the intention of patients in joining the IVF program.

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 objective of this chapter is to establish the positioning on Booking.com of hotels located in the cities of Tehran, Kashan, Abyaneh, Isfahan, Yazd, Persepolis, and Shiraz, the main tourism destinations in the Islamic Republic of Iran. The methodology is quantitative, consisting of the development of a “Spyder” that allows content to be identified and timely information to be extracted from the web. The data obtained allow to establish the average rating by the evaluation categories stated by the platform, while contributing to determining the strengths and weaknesses that the establishments present. These relevant data can thus contribute to the improvement of the services and the destination in general.

This chapter presents a summary of the literature on the influence of the Internet and other digital innovations on markets, consumers, and firms. The review leads to a list of topics in need of research in the general areas of big data, online and mobile advertising, consumer search, online privacy, online reviews, social networks, platforms for online transactions, and the impact of the Internet on retail markets, including multi-channel and omni-channel retailing. We discuss the big data approaches that have been applied to problems of targeting and positioning and suggest areas for further development of these approaches. We also discuss the emerging area of mobile advertising, which can further enhance targeting. On the consumer side, the evidence indicates that the Internet has greatly lowered the costs of search and access to retailers. Much of the consumer data are transmitted to sellers, and much of the online advertising is transmitted to consumers, through platforms, such as Google. We conclude that better models of competition among these platform firms are needed and that they need to be examined for anti-trust violations. While online retailing has grown rapidly, it still has a relatively small share of retail sales. Since sellers can combine the advantages of online and offline channels, it has been common for sellers to branch into multi-channel retailing. Given the increased availability of detailed consumer data, omni-channel selling, which emphasizes strategies for the various touchpoints that lead to a transaction, is an area for further development.

Social network analysis (SNA) may be useful in the exploration of the potential intersection between organizations, human relations (HR), public relations (PR), and corporate social responsibility (CSR) or sustainability issues. In an age of PR, social media have an important function, as reflected in the employee engagement movement. Visualization through mapping of Twitter data allows researchers to identify centers of social influence in which content travels through key accounts during sharing. Computer-mediated communication (CMC) concepts of identity, interaction, and community offer potential for future research.

Millions of ratings and reviews about products are available on the Internet for free, and they are used by academic researchers in the tourism sector. Data from websites like TripAdvisor are replacing or complementing traditional questionnaires and interviews. The authors are proposing a methodology to estimate the percentage accounted for by the sample of self-interviewed individuals over the total study population, in order to calculate the reliability of the results obtained. Average percentages obtained for hotels cannot be easily generalized due to the high dispersion in participation rates among hotels, even in the same city. Participation levels for tourist attractions are substantially lower than those for hotels and are likely biased, due to the fact that some tourists evaluate places without actually visiting them, merely after viewing them from the outside.