Old Wine in New Bottles?

by Charles Hofacker


Revisiting Electronic Word-of-Mouth, Special issue of the Journal of Business Research; Deadline 31 Oct 2021

POSTING TYPE: Calls: Journals

Author: Hongfei Liu

Journal of Business Research [Impact Factor: 4.874]

Special Issue:  Revisiting Electronic Word-of-Mouth (eWOM)Old Wine in New Bottles?

Submission deadline: 31-Oct-2021


Guest Editors

Dr. Hongfei Liu, University of Southampton, UK, hongfei.liu@soton.ac.uk

Professor Chanaka Jayawardhena, University of Surrey, UK, c.jayawardhena@surrey.ac.uk

Professor Paurav Shukla, University of Southampton, UK, p.v.shukla@soton.ac.uk

Dr. Victoria-Sophie Osburg, The University of Sheffield, UK, v.s.osburg@sheffield.ac.uk

Dr. Vignesh Yoganathan, The University of Sheffield, UK, v.yoganathan@sheffield.ac.uk

Call for Papers

Word-of-Mouth (WOM) as a marketing concept was introduced in the 1950s (Brooks Jr., 1957), and has been reinvigorated in the Internet age (Dellarocas, 2003). Almost two decades ago, Hennig-Thurau, Gwinner, Walsh & Gremler (2004) explored how the Internet age has allowed individual consumers to engage in Electronic Word-of-Mouth (eWOM) via consumer-opinion platforms. Despite these early efforts and ongoing attention devoted to the examination of eWOM from both academics and practitioners, there have been renewed calls for a more nuanced understanding of eWOM in order to maximize the business value (Babić Rosario, de Valck & Sotgiu, 2020). These calls have been legitimized in light of the ever-emerging and -evolving phenomena in the market – technological advancements, consumer’s attitudes towards marketing activities and online information, rising privacy concerns in the digital age, etc.

Against this backdrop, this Special Issue focuses on exploring the latest trends in eWOM research and practices beyond the prototype developed almost two decades ago (Hennig-Thurau et al., 2004). We welcome research that addresses the following question: What are the implications of the expansive and rapid changes driven by latest digital technologies and modern marketplace on consumers’ and other stakeholders’ eWOM behaviors and marketers’ eWOM practices and strategies? Given the rapid developments and wider implications of the topic in an information age, this call for papers will be intentionally broad. The following is not an exhaustive list, but provides some examples of potential directions and topics:

·       Beyond “positive and negative statement” – Reconceptualization of eWOM

eWOM, conceptualized as “any positive or negative statement made by potential, actual, or former customers about a product or company, which is made available to a multitude of people and institutions via the Internet”, is still widely acknowledged (Hennig-Thurau et al., 2004). However, as an ever-changing online phenomenon, eWOM message has various forms (e.g. text, image, video) and can be used across different marketing dynamics, for example, as a part of influencer marketing (Evans, Phua, Lim & Jun, 2017), seeded marketing (Chae, Stephen, Bart & Yao, 2017) and viral marketing (Borges-Tiago, Tiago & Cosme, 2019). This ever-widening evolution of the phenomena has perhaps not been captured in the prototyped conceptualization. Additionally, eWOM has been used interchangeably with other concepts (e.g. user-generated-content, online reviews and online recommendations). The commonness and distinctiveness between such concepts remain unclear. Therefore, we call for papers that reconceptualize eWOM in the modern age or distinguish eWOM from similar marketing concepts and applications possibly through conceptual study, document analysis, systematic literature review and meta-analysis.

·       Beyond Consumer-to-Consumer (C2C) communication – Expansion of the communication scope

eWOM is traditionally viewed as a C2C communication due to its voluntary and non-commercial nature (Libai et al., 2010). As businesses are increasingly aware of the impact of eWOM on firm performance, businesses have been devoting themselves to involving in eWOM communication by taking proactive and reactive actions (Wakefield & Wakefield, 2018). This has resulted in the transformation of eWOM from a C2C-only to B2C-friendly communication in the consumer market. Brands tend to foster positive eWOM or deal with negative eWOM in order to serve their marketing objectives. We, thus, highlight the strategic management of eWOM and encourage inquiries that explore the effectiveness of businesses’ engagement in eWOM communication. Meanwhile, B2B businesses increasingly embrace social media channels, including social networking sites (e.g. Facebook), blog sites (e.g. TypePad), social stream sites (e.g. app.net), professional networking sites (e.g. LinkedIn), review sites (e.g. Glassdoor), and video sites (e.g. Vimeo) (Iankova, Davies, Archer-Brown, Marder  & Yau, 2019). eWOM has been also initially observed in industrial marketing, and plays an increasingly important role in selling-purchasing mechanism in B2B marketplace (Steward, Narus & Roehm, 2018). Research that conceptualizes, theorizes and contextualize eWOM activities B2B market is welcomed.


·       Beyond consumers’ decision-making process – information-shaped consumer behaviors

Traditional view implants eWOM throughout the consumers’ decision-making process (e.g. eWOM-seeking pre-purchase and eWOM-giving post-purchase). While mobile technology dominates today’s market, it is easier than ever for consumers to access to and/or to be force-fed with an abundance of consumption-related information at any moment of daily life. Consumer behavior has also been shaped dramatically due to the information overloading. Consumers’ eWOM engaging behaviors (e.g. interactions between different parties regarding different information at different point of time) become increasingly diverse (Liu, Jayawardhena, Osburg & Babu, 2020), while the psychological mechanisms behind such behaviors are also different (Previte, Russell-Bennett, Mulcahy & Hartel, 2019). Therefore, we call for papers that examine consumers’ eWOM behaviors that are evolving with the changing marketplace and/or explain novel psychological mechanisms behind such behaviors.


·       Beyond online review sites and brands’ virtual communities – The rise of new digital media platforms

Digital Media disseminates eWOM, yet research on eWOM media/platforms remains fragmented. Early eWOM research either tends to focus on the online review sites highlighting antecedents and outcomes of review-based eWOM (e.g. Gretzel & Yoo, 2008) or emphasizes brands’ virtual communities (e.g. Facebook fan page) where social identity is key (Dholakia, Bagozzi & Pearo, 2004). Media differences for eWOM activities, consumers’ eWOM media preferences and cross-media eWOM engagement are underexplored (Xu & Lee, 2020). Additionally, the continued technological development and changes in consumer trends catalyze the emergence of new social media platforms, such as video-based social networking sites (e.g. Tik Tok and YouTube), photo-based social networking sites (e.g. Instagram and Pinterest) and multimedia mobile applications (e.g. Snapchat), and alternative approaches of content sharing, like temporary sharing (e.g. Instagram Story), live streaming (e.g. Facebook Live) and photo filter (Snapchat’s sponsored filter) (Roy, Datta & Mukherjee, 2019). We urge pioneering researchers to investigate the effectiveness of eWOM using the latest functions on new platforms.


·       Beyond a bunch of online reviews – The power of machine learning and big data

On Yelp, 150 million business reviews are generated monthly (Capoccia, 2018). There is no doubt that the increasing eWOM messages generate a pool of big data. Understanding eWOM by analyzing such big data through various tools (e.g. social listening, lexical analysis and statistical programming) allow academics and practitioners to understand the hidden clues that consumers left in the online environment and to interpret the deeper meanings behind consumers’ words. Meanwhile, the availability of big data facilitates the applications of machine learning in eWOM research and practices (Vermeer, Araujo, Bernritter & van Noort, 2019). Such techniques enable businesses to sustainably identify useful information that serves specific analytical purposes and enlightens business decisions. We welcome studies that capture consumer eWOM behaviors and business eWOM strategies using big data, and research employs machine learning techniques in interpreting eWOM phenomena.


  • Beyond fake reviews – The ethicality of eWOM communication

In the competitive market, some businesses commit ‘review fraud’, while creating fake reviews and eWOM messages across different media for themselves or their competitors becomes the most significant ethical issue in the eWOM communication (Luca & Zervas, 2016). Justifiably, in today’s society, ethicality attracts increasing attention in both business practices and Internet use. In terms of business ethics, a series of important questions remain underexplored, such as how ethicality-related eWOM influences consumers’ perceptions and brands’ performance, how eWOM enhances the effectiveness of brands’ CSR activities and ethical practices, how media owners and policy-makers address and prevent vicious competition through eWOM etc. (Chu, Chen & Gan, 2020). From the perspective of cyber- and techno-ethics, eWOM communication also highlights various ethical concerns. For example, eWOM messages as digital footprints left by consumers raise privacy concerns (Nam, Baker, Ahmad & Goo, 2020). Aggressive eWOM conversation could also trigger online bullying (Israeli, Lee & Karpinski, 2019). We look forward to receiving papers that investigate eWOM from the perspectives of consumer ethics, business ethics and cyber ethics.


·       Beyond consumers’ product/service recommendations – A multi-stakeholder and interdisciplinary view of eWOM

Naturally, consumers are key players in eWOM communication, and conversations are usually around the products or services of a particular brand. However, beyond real-life consumers, professional reviewers and influencers (see Bzzangent.com) increasingly engage in eWOM activities (Stubb & Colliander, 2019). More importantly, moving even further from the consumers’ perspective, latest observations suggest eWOM communication involves different parties and has an impact on multiple stakeholders, such as current and prospective employees (Stamolampros, Korfiatis, Chalvatzis & Buhalis, 2019), suppliers (Banerjee, Ries & Wiertz, 2020), competitors (Cao, 2019) and local communities (Uchinaka, Yoganathan & Osburg, 2019). In addition to the propensity of digital marketing, the digitalization has accelerated the transformation of various disciplines, while the power of eWOM has also been recognized across different disciplines, such as ‘digital finance’ (Cai, Lin, Xu, & Fu, 2016), ‘digital human resource management’ (Osburg, Yoganathan, Bartikowski, Liu & Strack, 2020) and ‘digital politics’ (Grover, Kar, Dwivedi, & Janssen, 2019). We look to receive research papers that take alternative stakeholders’ perspectives and/or investigate interdisciplinary phenomena led by eWOM.




Babić Rosario, A., de Valck, K., & Sotgiu, F. (2020). Conceptualizing the electronic word-of-mouth process: What we know and need to know about eWOM creation, exposure, and evaluation. Journal of the Academy of Marketing Science, 48, 422–448. https://doi.org/10.1007/s11747-019-00706-1

Banerjee, A., Ries, J. M., & Wiertz, C. (2020). The impact of social media signals on supplier selection: insights from two experiments. In Press International Journal of Operations & Production Management. https://doi.org/10.1108/ijopm-05-2019-0413

Borges-Tiago, M. T., Tiago, F., & Cosme, C. (2019). Exploring users’ motivations to participate in viral communication on social media. Journal of Business Research101, 574-582. https://doi.org/10.1016/j.jbusres.2018.11.011

Brooks Jr, R. C. (1957). “Word-of-mouth” advertising in selling new products. Journal of Marketing22(2), 154-161. https://doi.org/10.1177/002224295702200205

Cai, S., Lin, X., Xu, D., & Fu, X. (2016). Judging online peer-to-peer lending behavior: A comparison of first-time and repeated borrowing requests. Information & Management53(7), 857-867. https://doi.org/10.1016/j.im.2016.07.006

Cao, H. (2019). Online review manipulation by asymmetrical firms: Is a firm’s manipulation of online reviews always detrimental to its competitor?. Information & Management, 103244. https://doi.org/10.1016/j.im.2019.103244

Capoccia, C. (2018, April 11). Online Reviews Are the Best Thing That Ever Happened to Small Businesses. Retrieved from https://www.forbes.com/sites/forbestechcouncil/2018/04/11/

Chae, I., Stephen, A. T., Bart, Y., & Yao, D. (2017). Spillover effects in seeded word-of-mouth marketing campaigns. Marketing Science36(1), 89-104. https://doi.org/10.1287/mksc.

Chintagunta, P. K., Gopinath, S., & Venkataraman, S. (2010). The effects of online user reviews on movie box office performance: Accounting for sequential rollout and aggregation across local markets. Marketing Science29(5), 944-957. https://doi.org/10.1287/mksc.

Chu, S. C., Chen, H. T., & Gan, C. (2020). Consumers’ engagement with corporate social responsibility (CSR) communication in social media: Evidence from China and the United States. Journal of Business Research, 110, 260-271. https://doi.org/10.1016/j.jbusres.

Dellarocas, C. (2003). The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management Science49(10), 1407-1424. https://doi.org/10.1287

Dholakia, U. M., Bagozzi, R. P., & Pearo, L. K. (2004). A social influence model of consumer participation in network-and small-group-based virtual communities. International Journal of Research in Marketing21(3), 241-263. https://doi.org/10.1016/j.ijresmar.2003.12.004

Evans, N. J., Phua, J., Lim, J., & Jun, H. (2017). Disclosing Instagram influencer advertising: The effects of disclosure language on advertising recognition, attitudes, and behavioral intent. Journal of Interactive Advertising17(2), 138-149. https://doi.org/10.1080

Gretzel, U., & Yoo, K. H. (2008). Use and impact of online travel reviews. Information and Communication Technologies in Tourism 2008, 35-46. https://doi.org/10.1007/978-3-211-77280-5_4

Grover, P., Kar, A. K., Dwivedi, Y. K., & Janssen, M. (2019). Polarization and acculturation in US Election 2016 outcomes–Can twitter analytics predict changes in voting preferences. Technological Forecasting and Social Change145, 438-460. https://doi.org/10.1016/j.techfore.2018.09.009

Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet?. Journal of Interactive Marketing18(1), 38-52. https://doi.org/10.1002

Iankova, S., Davies, I., Archer-Brown, C., Marder, B., & Yau, A. (2019). A comparison of social media marketing between B2B, B2C and mixed business models. Industrial Marketing Management, 81, 169-179. https://doi.org/10.1016/j.indmarman.2018.01.001

Israeli, A. A., Lee, S. A., & Karpinski, A. C. (2019). The relationship between Internet addiction and negative eWOM. The Service Industries Journal, 39(13-14), 943-965. https://doi.org/10.1080/02642069.2018.1453501

Libai, B., Bolton, R., Bügel, M. S., De Ruyter, K., Götz, O., Risselada, H., & Stephen, A. T. (2010). Customer-to-customer interactions: broadening the scope of word of mouth research. Journal of Service Research13(3), 267-282. https://doi.org/10.1177/10946

Liu, H., Jayawardhena, C., Dibb, S., & Ranaweera, C. (2019). Examining the trade-off between compensation and promptness in eWOM-triggered service recovery: A restorative justice perspective. Tourism Management75, 381-392. https://doi.org/10.1016/j.tourman.

Liu, H., Jayawardhena, C., Osburg, V. S., & Babu, M. M. (2020). Do online reviews still matter post-purchase?. Internet Research, 30 (1), 109-139. https://doi.org/10.1108/intr-07-2018-0331

Luca, M., & Zervas, G. (2016). Fake it till you make it: Reputation, competition, and Yelp review fraud. Management Science, 62(12), 3412-3427. https://doi.org/10.1287/mnsc.2015.2304

Nam, K., Baker, J., Ahmad, N., & Goo, J. (2020). Determinants of writing positive and negative electronic word-of-mouth: Empirical evidence for two types of expectation confirmation. Decision Support Systems, 129, 113168. https://doi.org/10.1016/j.dss.2019.113168

Osburg, V. S., Yoganathan, V., Bartikowski, B., Liu, H., & Strack, M. (2020). Effects of ethical certification and ethical eWoM on talent attraction. Journal of Business Ethics, 164(3), 535-548. https://doi.org/10.1007/s10551-018-4018-8

Previte, J., Russell-Bennett, R., Mulcahy, R., & Hartel, C. (2019). The role of emotional value for reading and giving eWOM in altruistic services. Journal of Business Research99, 157-166. https://doi.org/10.1016/j.jbusres.2019.02.030

Roy, G., Datta, B., & Mukherjee, S. (2019). Role of electronic word-of-mouth content and valence in influencing online purchase behavior. Journal of Marketing Communications25(6), 661-684. https://doi.org/10.1080/13527266.2018.1497681

Stamolampros, P., Korfiatis, N., Chalvatzis, K., & Buhalis, D. (2019). Job satisfaction and employee turnover determinants in high contact services: Insights from Employees’ Online reviews. Tourism Management75, 130-147. https://doi.org/10.1016/j.tourman.2019.04.

Steward, M. D., Narus, J. A., & Roehm, M. L. (2018). An exploratory study of business-to-business online customer reviews: external online professional communities and internal vendor scorecards. Journal of the Academy of Marketing Science46(2), 173-189. https://doi.org/10.1007/s11747-017-0556-3

Stubb, C., & Colliander, J. (2019). “This is not sponsored content”–The effects of impartiality disclosure and e-commerce landing pages on consumer responses to social media influencer posts. Computers in Human Behavior, 98, 210-222. https://doi.org/10.1016

Uchinaka, S., Yoganathan, V., & Osburg, V. S. (2019). Classifying residents’ roles as online place-ambassadors. Tourism Management71, 137-150. https://doi.org/10.1016/j.tourman.2018.

Vermeer, S. A., Araujo, T., Bernritter, S. F., & van Noort, G. (2019). Seeing the wood for the trees: How machine learning can help firms in identifying relevant electronic word-of-mouth in social media. International Journal of Research in Marketing36(3), 492-508. https://doi.org/10.1016/j.ijresmar.2019.01.010

Wakefield, L. T., & Wakefield, R. L. (2018). Anxiety and ephemeral social media use in negative eWOM creation. Journal of Interactive Marketing41, 44-59. https://doi.org/10.1016/j.intmar.2017.09.005

Xu, X., & Lee, C. (2020). Utilizing the platform economy effect through EWOM: Does the platform matter?. International Journal of Production Economics227, 107663. https://doi.org/10.1016/j.ijpe.2020.107663