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Journal articles on the topic 'Word of mouth'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 March 2023

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1

Chong Lim, Boon, and Cindy M.Y. Chung. "Word-of-mouth." Asia Pacific Journal of Marketing and Logistics 26, no. 1 (January 7, 2014): 39–53. http://dx.doi.org/10.1108/apjml-02-2013-0027.

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Purpose – This research was designed to expand the understanding of how brand familiarity may affect the motivation to process word-of-mouth (WOM) information in brand evaluation. The pre-WOM brand attitude certainty is expected to explain the moderation effect. The paper aims to discuss these issues. Design/methodology/approach – Two experiments were conducted. The study participants were undergraduate students from a major university in Singapore. The main statistical analysis was done using a two-way analysis of covariance. Findings – The results of Experiments 1 and 2 support the prediction that consumers are more likely to use the perceived expertise of the WOM sender to evaluate an unfamiliar brand vs a familiar brand. Experiment 2 also provides some preliminary evidence that this interaction effect may be due to the difference in certainty of the study respondents in regards to the pre-WOM evaluation of unfamiliar and familiar brand. Research limitations/implications – This manipulation method of presenting WOM in a printed format may understate the impact of WOM. A more vivid manipulation of WOM that allows for a feedback loop may be considered for future research. Practical implications – The results highlight the importance of considering the strength dimensions of brand attitudes (e.g. attitude certainty) in the marketplace. For marketers of unfamiliar brands, source factors (e.g. expertise of WOM sender) are important to consider for effective use of WOM to market their products. For familiar brands, source factors are less relevant. Originality/value – This paper highlights the importance of considering attitude certainty and the subsequent malleability of attitude toward new information about the brand in the marketplace. Hence, marketers and researchers who are interested in changing brand attitude should take meta-attitude factors into consideration.

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2

Creelman, James. "Word of mouth." Managing Service Quality: An International Journal 2, no. 5 (May 1992): 299–301. http://dx.doi.org/10.1108/09604529210029551.

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3

Meuter, Matthew L., Deborah Brown McCabe, and James M. Curran. "Electronic Word-of-Mouth Versus Interpersonal Word-of-Mouth: Are All Forms of Word-of-Mouth Equally Influential?" Services Marketing Quarterly 34, no. 3 (July 2013): 240–56. http://dx.doi.org/10.1080/15332969.2013.798201.

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Kawakami, Tomoko, Kazuhiro Kishiya, and Mark E. Parry. "Personal Word of Mouth, Virtual Word of Mouth, and Innovation Use." Journal of Product Innovation Management 30, no. 1 (October 17, 2012): 17–30. http://dx.doi.org/10.1111/j.1540-5885.2012.00983.x.

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5

Keller, Ed, and Brad Fay. "Word-of-Mouth Advocacy." Journal of Advertising Research 52, no. 4 (December 2012): 459–64. http://dx.doi.org/10.2501/jar-52-4-459-464.

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6

Weiber, Rolf, and Tobias Wolf. "Word-of-Mouth Marketing." WiSt - Wirtschaftswissenschaftliches Studium 42, no. 4 (2013): 210–12. http://dx.doi.org/10.15358/0340-1650_2013_4_210.

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7

Groeger, Lars, and Francis Buttle. "Word-of-mouth marketing." European Journal of Marketing 48, no. 7/8 (July 8, 2014): 1186–208. http://dx.doi.org/10.1108/ejm-02-2012-0086.

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Purpose – The paper aims to provide a theoretically informed critique of current measurement practices for word-of-mouth marketing (WOMM) campaigns. Design/methodology/approach – An exploratory field study is conducted on a real-life WOMM campaign. Data are collected from two generations of campaign participants using a custom-built Facebook app and subjected to social network analysis (SNA). We compare our theoretically informed measure of campaign reach with industry standard practice. Findings – Standard metrics for WOMM campaigns assume campaign reach equates to the number of campaign-related conversations. These metrics fail to allow for the possibility that some participants may be exposed multiple times to campaign-related messaging. In this exploratory field study, standard metrics overestimate campaign reach by 57.5 per cent. The campaign is also significantly less efficient in terms of cost-per-conversation. SNA shows that multiple exposures are associated with transitivity and tie strength. Multiple exposures mean that the total number of campaign-related conversations cannot be regarded as equivalent to the number of individuals reached. Research limitations/implications – SNA provides a sound theoretical foundation for the critique of current WOMM measurement practices. Two social-structural network attributes – transitivity and tie strength – inform our critique. A single WOMM campaign provides the field study context. Practical implications – The findings have significant implications for the development and deployment of WOMM effectiveness and efficiency metrics and are relevant to WOMM agencies, agency clients and the Word-of-Mouth Marketing Association. Originality/value – This is the largest field study of its kind having collected data on >5,000 WOMM campaign-related conversations. Participants specified precisely whom they spoke to about the campaign and the strength of that social tie. This is the first SNA-informed critique of standard WOMM campaign measurement practices and first quantification of offline multiple exposures to a WOMM campaign. We demonstrate how standard campaign metrics are based on the false assumption that word-of-mouth flows exclusively along intransitive ties.

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8

Simpson, Penny M., and Judy A. Siguaw. "Destination Word of Mouth." Journal of Travel Research 47, no. 2 (July 7, 2008): 167–82. http://dx.doi.org/10.1177/0047287508321198.

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Ring, Amata, Aaron Tkaczynski, and Sara Dolnicar. "Word-of-Mouth Segments." Journal of Travel Research 55, no. 4 (December 10, 2014): 481–92. http://dx.doi.org/10.1177/0047287514563165.

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10

Banerjee, Abhijit, and Drew Fudenberg. "Word-of-mouth learning." Games and Economic Behavior 46, no. 1 (January 2004): 1–22. http://dx.doi.org/10.1016/s0899-8256(03)00048-4.

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11

Singh, Deepali. "Electronic Word of Mouth." Paradigm 4, no. 2 (July 2000): 1–11. http://dx.doi.org/10.1177/0971890720000202.

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12

East, Robert. "Researching Word of Mouth." Australasian Marketing Journal (AMJ) 15, no. 1 (January 2007): 23–26. http://dx.doi.org/10.1016/s1441-3582(07)70025-3.

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13

Fong, John, and Suzan Burton. "Elecronic Word-of-Mouth." Journal of Interactive Advertising 6, no. 2 (March 2006): 7–62. http://dx.doi.org/10.1080/15252019.2006.10722119.

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14

Ahrens, Jan, James R. Coyle, and Michal Ann Strahilevitz. "Electronic word of mouth." European Journal of Marketing 47, no. 7 (July 19, 2013): 1034–51. http://dx.doi.org/10.1108/03090561311324192.

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15

Schmidt-Nielsen, Knut. "By Word of Mouth." Physiology 1, no. 3 (June 1, 1986): 85. http://dx.doi.org/10.1152/physiologyonline.1986.1.3.85.

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Lis, Bettina, and Christian Neßler. "Electronic Word of Mouth." Business & Information Systems Engineering 6, no. 1 (December 21, 2013): 63–65. http://dx.doi.org/10.1007/s12599-013-0306-0.

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17

Burnham, Thomas A., and R. Bret Leary. "WORD OF MOUTH OPPORTUNITY: WHY RECOMMENDATION LIKELIHOOD OVERESTIMATES POSITIVE WORD OF MOUTH." Journal of Marketing Theory and Practice 26, no. 4 (October 2, 2018): 368–89. http://dx.doi.org/10.1080/10696679.2018.1487770.

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18

Mitić, Sanja. "Word of mouth on the Internet: Cross-cultural analysis." Marketing 51, no. 2 (2020): 88–97. http://dx.doi.org/10.5937/markt2002088m.

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19

Brenner, Paul, and Ellen M. McGee. "Case Study: Word of Mouth." Hastings Center Report 26, no. 4 (July 1996): 19. http://dx.doi.org/10.2307/3527602.

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20

Krishnan, Suraj, and L. C. "Word of Mouth Marketing Strategy." International Journal of Computer Applications 182, no. 2 (July 16, 2018): 1–6. http://dx.doi.org/10.5120/ijca2018917447.

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21

&NA;. "Word-of-mouth works best." Inpharma Weekly &NA;, no. 953 (September 1994): 6. http://dx.doi.org/10.2165/00128413-199409530-00010.

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22

Lee, Mira, and Seounmi Youn. "Electronic word of mouth (eWOM)." International Journal of Advertising 28, no. 3 (January 2009): 473–99. http://dx.doi.org/10.2501/s0265048709200709.

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23

Blazevic, Vera, Wafa Hammedi, Ina Garnefeld, Roland T. Rust, Timothy Keiningham, Tor W. Andreassen, Naveen Donthu, and Walter Carl. "Beyond traditional word‐of‐mouth." Journal of Service Management 24, no. 3 (June 14, 2013): 294–313. http://dx.doi.org/10.1108/09564231311327003.

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24

Wangenheim, Florian v. "Postswitching Negative Word of Mouth." Journal of Service Research 8, no. 1 (August 2005): 67–78. http://dx.doi.org/10.1177/1094670505276684.

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25

Haywood, K. Michael. "Managing Word of Mouth Communications." Journal of Services Marketing 3, no. 2 (February 1989): 55–67. http://dx.doi.org/10.1108/eum0000000002486.

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26

Martin, William C., and Jason E. Lueg. "Modeling word-of-mouth usage." Journal of Business Research 66, no. 7 (July 2013): 801–8. http://dx.doi.org/10.1016/j.jbusres.2011.06.004.

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27

Groeger, L., and F. Buttle. "Deciphering Word-of-Mouth Marketing Campaign Reach: Everyday Conversation Versus Institutionalized Word of Mouth." Journal of Advertising Research 56, no. 4 (December 1, 2016): 368–84. http://dx.doi.org/10.2501/jar-2016-043.

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28

Toder-Alon, Anat, and Frédéric F. Brunel. "Peer-to-peer word-of-mouth: word-of-mouth extended to group online exchange." Online Information Review 42, no. 2 (April 9, 2018): 176–90. http://dx.doi.org/10.1108/oir-09-2016-0290.

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Purpose The purpose of this paper is to investigate how peer-to-peer word-of-mouth (PPWOM) conversations evolve over time because of the dynamic social nature of the community in which they take place. Design/methodology/approach This study analyzed PPWOM conversations in an online community website for new and expectant mothers. Two data collection phases were undertaken during a four-year period. In phase I, messages were collected for a one-month period from five different bulletin boards (i.e. cross-sectional data) and at two points in time (i.e. semi-longitudinal). In phase II, a full longitudinal study was conducted, and the complete text of all messages of a newly formed bulletin board was captured for a nine-month period. The corpus of messages was examined in line with the basic tools of ethnomethodology and conversation analysis. Findings This research developed a typology of PPWOM genres and showed that these genres change over the community lifespan. The findings confirmed that the levels of social cohesiveness and the interaction communicative motives are the main factors that distinguish different PPWOM genres. Research limitations/implications This research has offered a new perspective into the study of PPWOM, and hopefully it will serve as a starting point for a broader dialogue regarding the social context in which PPWOM is exchanged. Originality/value In contrast to traditional word-of-mouth research, this study demonstrated that PPWOM conversations go much beyond the exchange of functional information, and instead serve numerous social and emotional goals.

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29

Zen-U Hotta and Masato Eguchi. "VOTING BEHAVIOR RESPONSES TO WOM (WORD-OF-MOUTH) AND EWOM (ELECTRONIC WORD-OF-MOUTH) INFORMATION." Political Studies 17, no. 505 (February 25, 2023): 111–21. http://dx.doi.org/10.22353/ps.v17i505.2512.

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Decision making is often influenced by external information, especially opinions of others.Though past studies revealed that both WOM (word-of-mouth) and EWOM (electronic word-of-mouth) information influences on decision making, little has been investigated and found out in the field of voting behavior, with the possible exception of the fact that several categories of WOM factors influence on voting. As voters face multiple WOM and EWOM information concerning various characteristics of political candidates in real life, it is important to know how they prioritize some information over others. On such backdrop, this study attempts to see how much weight voters would put on 640 types of information – positive and negative information on 16 types of candidate characteristics coming from 20 different WOM and EWOM sources. Two facts have come out. One is that voters prioritize positive information over negative information of the same candidate characteristic, with the exceptions of relationship with family members, campaign activity, and news/scandal of candidate.Another is that voters prioritize WOM information over EWOM information on the same candidate characteristic, regardless of whether the information is positive or negative, for all characteristics.

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30

Alexander, Daniel, Eti Dwi Wiraningsih, and Lukita Ambarwati. "Word Of Mouth, Mathematics Analisis Kestabilan Pemodelan Matematika Penyebaran Word Of Mouth Berbasis Brand Community." JMT : Jurnal Matematika dan Terapan 5, no. 1 (February 28, 2023): 19–32. http://dx.doi.org/10.21009/jmt.5.1.3.

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Pemasaran word of mouth berbasis brand community membuat perusahaan menargetkan komunitas-komunitas yang sesuai dengan karakteristik produk yang membuat pemasaran word of mouth menjadi lebih efektif. Penelitian ini berfokus pada pemodelan dan analisis pemasaran word of mouth berbasis brand community. Model terdiri dari lima variabel yaitu Susceptible, Infected, Community, Positive, dan Negative. Model dianalisis dengan menentukan titik kesetimbangan yang menghasilkan dua titik kesetimbangan yaitu titik kesetimbangan yang didapatkan saat tidak ada individu terinfeksi dan titik kesetimbangan yang didapatkan saat terdapat individu terinfeksi. Simulasi menggunakan data yang telah diperoleh dari salah satu perusahaan di Indonesia, dengan nilai bilangan reproduksi dasar sebesar 950,1458877.

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31

Saini, Rutika, and H. K. Dangi. "Word of Mouth to Word of Mouse: A Study." Effulgence-A Management Journal 16, no. 1 (January 1, 2018): 51. http://dx.doi.org/10.33601/effulgence.rdias/v16/i1/2018/51-60.

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32

Minh Sang, Nguyen. "Corporate social responsibility, electronic word-of-mouth and customer loyalty in Vietnam’s banking sector." Banks and Bank Systems 17, no. 3 (August 18, 2022): 38–48. http://dx.doi.org/10.21511/bbs.17(3).2022.04.

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This research explored and examined the link between electronic word-of-mouth, corporate social responsibility, and loyalty of 282 customers using banking services in Vietnam (PLS-SEM) through the Partial Least Squares Structural Equation Modeling. The data were gathered using convenience sampling, with a sample of 282 customers who used banking services in Vietnam and interacted with the bank through social media. The survey is intended to include 16 questions separated into two parts: the first part contains 5 demographic questions, and the second part contains 11 questions divided into three sets of factors: corporate social responsibility, electronic word-of-mouth, and loyalty. The survey was emailed to customers using banking services and interacting with banks via social media in Vietnam. According to the findings of the empirical study, there is a direct and indirect link between corporate social responsibility, electronic word-of-mouth, and customer loyalty in Vietnam’s banking sector. The results of empirical research in Vietnam’s banking industry indicate that corporate social responsibility has direct and positive impact on customer loyalty; corporate social responsibility has a direct and positive impact on customer’s word-of-mouth; electronic word-of-mouth has a direct and positive impact on customer loyalty; and finally, corporate social responsibility has an indirect impact on customer loyalty through customer’s electronic word-of-mouth. AcknowledgmentThe author would like to thank all the customers who completed the survey. The author would like to thank all parties and the Banking University of Ho Chi Minh City for their excellent support and assistance in completing this research.

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33

GILDIN, SUZANA Z. "Understanding the Power of Word-of-Mouth." RAM. Revista de Administração Mackenzie 4, no. 1 (June 2003): 92–106. http://dx.doi.org/10.1590/1678-69712003/administracao.v4n1p92-106.

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ABSTRACT Word-of-mouth has been considered one of the most powerful forms of communication in the market today. Understanding what makes word-of-mouth such a persuasive and powerful communication tool is important to organizations that intend to build strong relationships with consumers. For this reason, organizations are concerned about promoting positive word-of-mouth and retarding negative word-of-mouth, which can be harmful to the image of the company or a brand. This work focuses on the major aspects involving word-of-mouth communication. Recommendations to generate positive word-of-mouth and retard negative word-of-mouth are also highlighted.

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34

Sugianto, La Ode. "ANTECEDENT AND KONSEKUEN WORD OF MOUTH." Equilibrium: Jurnal Ekonomi Syariah 4, no. 1 (February 13, 2017): 155. http://dx.doi.org/10.21043/equilibrium.v4i1.1635.

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<p><em>This research intended to analyze the antecedent and consequent of word of mouth at Sultan Agung Islamic University, Semarang. After distributing the relevant questionnaires to 99 students or research subjects, all usable questionnaires were returned. Then the collected data were analyzed by using Structural Equation Modeling with Smart PLS 3.0 software. Research findings showed that institution image has positive significant effect on word of mouth and students’ loyalty. Furthermore students’ satisfaction has positive significant effect on word of mouth and students’ loyalty. The word of mouth also has positive significant effect on loyalty. Moreover, Islamic academic culture can moderate the correlation between students’ satisfaction and word of mouth in Sultan Agung Islamic University, Semarang.</em></p>

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35

Drapińska, Anna. "Współczesny Word of Mouth – dylematy pojęciowe." Zarządzanie Mediami 9, no. 2 (2021): 191–206. http://dx.doi.org/10.4467/23540214zm.21.012.13407.

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Contemporary Word of Mouth – Conceptual Dilemmas Word of mouth is one of the most important factors that affect customers when making purchases and making purchasing decisions. The growing number of its new forms and the increasingly complex nature, caused a lot of ambiguities and difficulties both in conducting research on this phenomenon and in the implementation of effective marketing activities. Therefore, the purpose of this chapter is to organize the most important concepts and concepts related to WOM communication, based on current global research results. The chapter identifies and defines the most important concepts related to WOM, including traditional WOM, eWOM and sWOM. Furthermore, the main differences between them are identified. Finally, the necessary directions for further research in this area were indicated.

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36

Lan, Meei-Ying, Fangyi Liu, Cheng-Hsi Fang, and Tom M. Y. Lin. "Understanding Word-of-Mouth in Counterfeiting." Psychology 03, no. 03 (2012): 289–95. http://dx.doi.org/10.4236/psych.2012.33041.

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37

Nurcaya, I. Nyoman, and Ni Made Purnami. "Brand Engagement and Word of Mouth." Udayana Journal of Social Sciences and Humanities (UJoSSH) 1, no. 1 (February 27, 2017): 85. http://dx.doi.org/10.24843/ujossh.2017.v01.i01.p14.

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Modern marketing using social media such as Facebook allow the marketers to have a two-way interaction with the consumers, let them give appreciation each other, allow the consumers to leave comments about the products, and the company can directly provide answers to the consumers’ questions and complaints. The purpose of this study is to examine the effect of brand engagement on word of mouth. This research was conducted in Denpasar. The respondents are those who have clicked “like”, “share”, or “comment” button upon a particular brand on Facebook. The data were collected by distributing questionnaires to the respondents who have met the criteria. This study used Partial Least Square (PLS) analysis technique. The results show that 1) Inner self has positive and significant impact on brand love Oriflame; 2) Social self has positive and significant impact on brand love Oriflame; 3) Brand love has positive and significant impacton Word of Mouth Oriflame on Facebook.

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38

Kamada, Yuichiro, and Aniko Öry. "Contracting with Word-of-Mouth Management." Management Science 66, no. 11 (November 2020): 5094–107. http://dx.doi.org/10.1287/mnsc.2019.3417.

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We propose a model for word-of-mouth (WoM) management where a firm has two tools at hand: offering referral rewards and offering a free contract. Current customers’ incentives to engage in WoM can affect the contracting problem of a firm in the presence of positive externalities of users. Formally, we consider a classic Maskin–Riley contracting problem for the receiver of WoM where the firm can pay the senders referral rewards and a sender experiences positive externalities if the receiver adopts. A free contract can incentivize WoM because the higher adoption probability increases the expected externalities that the sender receives. We characterize the optimal incentive scheme and show when the two tools serve as substitutes and complements to each other depending on whether the market is niche and whether the product is social. We show that offering a free contract is optimal only if the fraction of premium users in the population is small, which is consistent with the observation that companies that successfully offer “freemium” contracts oftentimes have a high percentage of free users. This paper was accepted by Juanjuan Zhang, marketing.

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39

Horner, Richard. "Spread the word about mouth cancer." Vital 7, no. 5 (October 2010): 47–49. http://dx.doi.org/10.1038/vital1288.

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40

COHEN, MICHAEL R. "You canʼt trust word of mouth." Nursing 33, no. 2 (February 2003): 14. http://dx.doi.org/10.1097/00152193-200302000-00010.

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41

Chan, Yolanda Y. Y., and E. W. T. Ngai. "Conceptualising electronic word of mouth activity." Marketing Intelligence & Planning 29, no. 5 (August 2, 2011): 488–516. http://dx.doi.org/10.1108/02634501111153692.

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42

Ferguson, Ronald J., Michele Paulin, and Elizabeth Leiriao. "Loyalty and Positive Word-of-Mouth." Health Marketing Quarterly 23, no. 3 (January 1, 2006): 59–77. http://dx.doi.org/10.1080/07359680802086174.

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Greenwood, Leigh. "Word of mouth: promoting oral health." Dental Nursing 4, no. 2 (February 2008): 71–72. http://dx.doi.org/10.12968/denn.2008.4.2.29930.

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44

Schellekens, Gaby A. C., Peeter W. J. Verlegh, and Ale Smidts. "Language Abstraction in Word of Mouth." Journal of Consumer Research 37, no. 2 (August 2010): 207–23. http://dx.doi.org/10.1086/651240.

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45

Anderson, Eugene W. "Customer Satisfaction and Word of Mouth." Journal of Service Research 1, no. 1 (August 1998): 5–17. http://dx.doi.org/10.1177/109467059800100102.

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46

Kimmel, Allan J., and Philip J. Kitchen. "Word of mouth and social media." Journal of Marketing Communications 20, no. 1-2 (December 20, 2013): 2–4. http://dx.doi.org/10.1080/13527266.2013.865868.

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Lovett, Mitchell J., Renana Peres, and Ron Shachar. "On Brands and Word of Mouth." Journal of Marketing Research 50, no. 4 (August 2013): 427–44. http://dx.doi.org/10.1509/jmr.11.0458.

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48

Campbell, Arthur, C. Matthew Leister, and Yves Zenou. "Word‐of‐mouth communication and search." RAND Journal of Economics 51, no. 3 (August 27, 2020): 676–712. http://dx.doi.org/10.1111/1756-2171.12337.

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49

Cloonan, Thomas F. "Word of Mouth." PsycCRITIQUES 55, no. 52 (2010). http://dx.doi.org/10.1037/a0021943.

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"Word of Mouth." Word of Mouth 20, no. 1 (September 2008): 1–16. http://dx.doi.org/10.1177/10483950080200010101.

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