Abstract:
Gruen, Osmonbekov, & Czaplewski (2006) argue that social media have totally broken the concepts of traditional marketing by raising the important role of e-WOM exchange via social media platforms. In fact, social media have extended WOM networks “from one’s immediate contacts to the entire Internet world” (Cheung, Lee, & Rabjohn, 2008, p.10). With extraordinary growth of Internet-based media, the recent literature
has confirmed the persuasive power of e-WOM on consumer choices by informing,
motivating, influencing opinions and providing recommendations for products and
services ( Racherla & King, 2012). However, in social networking context, when online WOM
arises from unlimited electronic sources with unknown producers, the validity
of information becomes more uncertain and unreliable (Cheung et
al., 2008). Consequently, it
is prudent to explore how consumers evaluate and adopt online WOM messages,
which in turn affects their purchase decisions. This phenomenon, called “the adoption
of online opinions”, which has not been well investigated, is the central point
of the exploratory research presented here. Moreover, this study is useful and
meaningful when being conducted in New Zealand market, where young people account
for the largest proportion (23.55%) of total social media users in 2012 (White, 2012).
This research employs the mixed-method approach with focus groups and a large scale survey in New Zealand context. The integrated research strategy provides greater opportunity to acquire in-depth understanding and a wider view about determinants of e-WOM adoption via social media platforms among young consumers. It is expected that the findings enable researchers and practitioners to gain fascinating insights into how contemporary youth seek and accept online WOM messages from social media for their consumption decisions. From analyzing these factors, marketers can outline effective methods to better promote products/services via social media platforms or develop customer social networks with useful information presentation to speed up the consumer decision process.
This research employs the mixed-method approach with focus groups and a large scale survey in New Zealand context. The integrated research strategy provides greater opportunity to acquire in-depth understanding and a wider view about determinants of e-WOM adoption via social media platforms among young consumers. It is expected that the findings enable researchers and practitioners to gain fascinating insights into how contemporary youth seek and accept online WOM messages from social media for their consumption decisions. From analyzing these factors, marketers can outline effective methods to better promote products/services via social media platforms or develop customer social networks with useful information presentation to speed up the consumer decision process.
Useful references
A. Books:
Useful - Must refer to
1) Cakim, I. M. (2010). Implementing word of mouth marketing: Online strategies to identify influencers, craft stories, and draw customers. Hoboken, N.J: Wiley.
Call number: HF5827.95 .C35 2010 – University of Waikato Library, Central library – Level 3
2) Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (2nd ed.). Thousand Oaks, Calif: Sage Publications.
Call number: H62 .C71 2009 – University of Waikato Library, Central library – Level 3
3) Golden, M. (2011). Social media strategies for professionals and their firms: The guide to establishing credibility and accelerating relationships. N.J.: Wiley.
Call number: HF5415.1265 .G63 2011 – University of Waikato Library, Central library – Level 3
4) Qualman, E. (2009). Socialnomics: How social media transforms the way we live and do business. Hoboken, N.J: Wiley.
Call number: HF5415.1265 Q83 2009 – University of Waikato Library, Central library – Level 3
Useful – Worth considering
1) Brown, D. (2008). Influencer marketing: Who really influences your customers? Amsterdam ; Oxford: Elsevier/Butterworth-Heinemann.
Call number: HF5414 .B76 2008 – University of Waikato Library, Central library – Level 3
2) Bryman, A., & Bell, E. (2011). Business Research Methods (3rd ed.). Oxford: Oxford University Press.
Call number: HD30.4 .B79 2011 – University of Waikato Library, Central library – Level 3
3) Sterne, J., & ebrary, Inc. (2010). Social media metrics: How to measure and optimize your marketing investment. Hoboken, N.J: Wiley.
Retrieved from http://site.ebrary.com/lib/waikato/Doc?id=10377809
Low value – Can ignore
1) Brown, R. (2009). Public relations and the social web: Using social media and Web 2.0 in communications. London ; Philadelphia: Kogan Page.
Call number: HM1221 .B76 2009 – University of Waikato Library, Central library – Level 3
2) Safko, L. (2009). The social media bible: Tactics, tools, and strategies for business success. Hoboken, N.J: John Wiley & Sons.
Call number: HF5415.1265 .S24 2009 – University of Waikato Library, Central library – Level 3
B. Articles:
Useful - Must refer to
1) Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An Elaboration Likelihood Model. MIS Quarterly, 30(4), 805–825. doi:10.2307/25148755.
Abstract: This study examines how processes of external influence shape information technology acceptance among potential users, how such influence effects vary across a user population, and whether these effects are persistent over time. Drawing on the elaboration-likelihood model (ELM), the authors compared two alternative influence processes, the central and peripheral routes, in motivating IT acceptance.
These processes were respectively operationalized using the argument quality and source credibility constructs, and linked to perceived usefulness and attitude, the core perceptual drivers of IT acceptance. This study contributes to the IT acceptance literature by introducing ELM as a referent theory for acceptance research, by elaborating alternative modes of influence, and by specifying factors moderating their effects.
Web link: http://www.jstor.org.ezproxy. waikato.ac.nz/ stable/10.2307/25148755
2) Brown, J., Broderick, A. J., & Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. Journal of interactive marketing, 21(3), 2–20.
Abstract: The authors report the results of a two-stage study aimed at investigating online WOM: a set of in-depth qualitative interviews followed by a social network analysis of a single online community. The results provide strong evidence that individuals behave as if Web sites themselves are primary “actors” in social networks and that online communities can act as a social proxy for individual identification. The authors offer a conceptualization of online social networks which takes the Web site into account as an actor,an initial exploration of the concept of a consumer–Web site relationship, and a conceptual model of the online interaction and information evaluation process.
Web link: http://www.sciencedirect.com.ezproxy.waikato.ac.nz/science/article/pii/S1094996807700300
3) Cheung, C. M. K., Lee, M. K. O., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Research, 18(3), 229–247.
Abstract: The paper examines the extent to which opinion seekers are willing to accept and adopt online consumer reviews and which factors encourage adoption. Using dual-process theories, an information adoption model was developed to examine the factors affecting information adoption of online opinion seekers. The model was tested empirically using a sample of 154 users who had experience within the online customer community, Openrice.com. Users were required to complete a survey regarding the online consumer reviews received from the virtual sharing platform.The paper found comprehensiveness and relevance to be the most effective components of the argument quality construct of the research model, making them key influencers of information adoption.
Web link:http://search.proquest.com. ezproxy.waikato.ac.nz/docview /219845247
4) Cheung, M. Y., Luo, C., Sia, C. L., & Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of online consumer recommendations. International Journal of Electronic Commerce, 13(4), 9–38. doi:10.2753/JEC1086-4415130402
Abstract:Word-of-mouth (WOM) study is extended to the on-line context (eWOM) by examining the informational and normative determinants of the perceived credibility of on-line consumer recommendations. A survey of users of an on-line consumer discussion forum in China substantiated the effects of the determinants, although post-hoc analyses revealed that prior knowledge and involvement level moderate some of them. Implications for research and practice are discussed.
Web link: http://web.ebscohost.com.ezproxy.waikato.ac.nz/ehost/detail?sid=09a81f36-790e-4d85-aa04-258fda79dc7b%40sessionmgr198&vid=1&hid=117&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=buh&AN=41423245
5) Flanagin, A. J., & Metzger, M. J. (2008). Digital media and youth: Unparalleled opportunity and unprecedented responsibility. Digital Media, Youth, and Credibility, 5–27.
Abstract:The article examines the major issues with regard to credibility and, in particular, what special concerns arise for youth populations. This volume represents a first step toward mapping that complexity and providing a basis for future work that seeks to find explanations that will ultimately help scholars, educators, policymakers, and youth take advantage of the new opportunities for empowerment and learning offered by digital networked media.
Web link: http://mitpress2.mit.edu/ books/chapters /0262562324chap1.pdf
6) Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006). E-WOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty. Journal of Business Research, 59(4), 449–456. doi:10.1016/j.jbusres.2005.10.004
Abstract: This paper investigates the effects of a specific form of electronic word-of-mouth (eWOM) communication, customer-to-customer know-how exchange, on customer perceptions of value and customer loyalty intentions. In addition, the paper explores the antecedents of customer-to-customer know-how exchange overlooked in prior research: motivation, opportunity, and ability. The survey results from 616 participants of an online forum suggest that customer know-how exchange impacts customer perceptions of product value and likelihood to recommend the product, but does not influence customer repurchase intentions. Interestingly, opportunity did not impact know-how exchange, whereas motivation and ability did have a significant effect
Web link: http://www.sciencedirect.com.ezproxy.waikato.ac.nz/science/article/pii/S0148296305001517
7) 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 Marketing, 18(1), 38–52. doi:10.1002/dir.10073
Abstract: The Internet makes it possible for consumers to obtain electronic word of mouth from other consumers. Customer comments articulated via the Internet are available to a vast number of other customers, and therefore can be expected to have a significant impact on the success of goods and services. This paper derives several motives that explain why customers retrieve other customers' on-line articulations from Web-based consumer opinion platforms. The relevance of these motives and their impact on consumer buying and communication behavior are tested in a large-scale empirical study. The results illustrate that consumers read on-line articulations mainly to save decision-making time and make better buying decisions. Structural equation modeling shows that their motives for retrieving on-line articulations strongly influence their behavior.
Web link: http://web.ebscohost.com.ezproxy.waikato.ac.nz/ehost/detail?sid=a2911a79-377c-4fe2-bebd-eb5960f8df48%40sessionmgr115&vid=1&hid=117&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=buh&AN=12302034
8) Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business horizons, 53(1), 59–68.
Abstract: The concept of Social Media is top of the agenda for many business executives today. Decision makers, as well as consultants, try to identify ways in which firms can make profitable use of applications such as Wikipedia, YouTube, Facebook, Second Life, and Twitter. Yet despite this interest, there seems to be very limited understanding of what the term “Social Media” exactly means; this article intends to provide some clarification. The authors begin by describing the concept of Social Media, and discuss how it differs from related concepts such as Web 2.0 and User Generated Content. Based on this definition, the authors then provide a classification of Social Media which groups applications currently subsumed under the generalized term into more specific categories by characteristic: collaborative projects, blogs, content communities, social networking sites, virtual game worlds, and virtual social worlds. Finally, we present 10 pieces of advice for companies which decide to utilize Social Media.
Web link: http://www.sciencedirect.com.ezproxy.waikato.ac.nz/science/article/pii/S0007681309001232
9) McKnight, H., & Kacmar, C. (2006). Factors of information credibility for an internet advice site. In System Sciences, 2006. HICSS’06. Proceedings of the 39th Annual Hawaii International Conference on (Vol. 6, p. 113b–113b). Retrieved from http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1579516
Abstract: Information credibility is important to Internet advice site vendors because they primarily build a revenue stream based on how credible consumers consider the information on the website. Unless consumers believe the website’s information is credible, they are not likely to be willing to act on the advice. This paper reports on an empirical study of how individual differences and initial site impressions affect perceptions of website information credibility. Results confirm that most of the proposed individual difference and initial impression variables play an important role in how consumers view the credibility of an unfamiliar website. Implications are included regarding adapting websites to take into account initial site impressions and individual differences.
Web link: http://ieeexplore.ieee.org /xpls /abs_all.jsp?arnumber =1579516
10) Needham, A. (2008). Word of mouth, youth and their brands. Young Consumers: Insight and Ideas for Responsible Marketers, 9(1), 60–62.
Abstract: Using Headbox, a researc and seeding community for 30,000 16-25 year olds who share their thoughts, their opinions and their ideas and get rewarded for it, consumer insights on brands and how positive and negative WOM are described. The paper finds that the importance of co-creation is vital in diffusion. Co-creation implies that marketing happens with young people rather than it being directed at them. Managerial implications suggest a new mindset toward marketing and greater emphasis on the active role of social communities in the youth market. A new approach to marketing using social networking and a very large sample suggests that we are near to a clearer understanding of the complexities of diffusion by WOM.
Web link: http://www.emeraldinsight.com.ezproxy.waikato.ac.nz/journals.htm?articleid=1714964&show=abstract
11) O’Reilly, K., & Marx, S. (2011). How young, technical consumers assess online WOM credibility. Qualitative Market Research: An International Journal, 14(4), 330–359.
Abstract: Analysis shows that participants exhibit more of a “bricks-to-clicks” than a “clicks-to-bricks” purchasing cycle. In addition to relying on customer reviews online, participants accept online WOM to enhance their self-worth, avoid risk, or enact negativity bias. Additionally, assessment of online WOM credibility is based on four factors: the polarity and quantity of posts, the logic and articulation of posts, the ability to find corroborating sources, and the previous experience of participants with particular sellers.
Web link: http://www.emeraldinsight.com.ezproxy.waikato.ac.nz/journals.htm?articleid=1950949&show=abstract
12) Racherla, P., & King, R. (2012). What we know and don’t know about online word-of-mouth: A systematic review and synthesis of the literature (SSRN Scholarly Paper No. ID 2187040). Rochester, NY: Social Science Research Network.
Abstract: Based on a systematic review of 148 studies, the authors conduct a multi-dimensional analysis of e-WOM communication, consumption and effects. Results show that the factors that drive consumers to generate/transmit e-WOM include need for self-enhancement, social interaction and altruism. These factors also assure the generation of quality information that benefits consumers who seek eWOM. The findings indicate that the effects of eWOM on consumer and market-level outcomes are not linear and vary significantly owing to eWOM dimensions such as valence and volume, and across products and consumers. With social media and other eWOM platforms taking central stage in marketing and promotional strategies, it is important to consider the key effects of eWOM on metrics such as consumer loyalty, life-time value and service delivery costs.
Web link: http://papers.ssrn.com/abstract=2187040
13) Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 14(1), 47–65. doi:10.1287/isre.14.1.47.14767
Abstract: This research investigates how knowledge workers are influenced to adopt the advice that they receive in mediated contexts. The research integrates the Technology Acceptance Model with dual-process models of informational influence. The model is investigated qualitatively first, using interviews of a sample of 40 consultants, and then quantitatively on another sample of 63 consultants from the same international consulting organization. Data reflect participants' perceptions of actual e-mails they received from colleagues consisting of advice or recommendations. Results support the model, suggesting that the process models used to understand information adoption can be generalized to the field of knowledge management, and that usefulness serves a mediating role between influence processes and information adoption. Organizational knowledge work is becoming increasingly global. This research offers a model for understanding knowledge transfer using computer-mediated communication.
Web link: http://isr.journal.informs.org.ezproxy.waikato.ac.nz/content/14/1/47.full.pdf
14) Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site. Journal of Marketing, 73(5), 90–102
Abstract: The authors study the effect of word-of-mouth (WOM) marketing on member growth at an Internet social networking site and compare it with traditional marketing vehicles. Because social network sites record the electronic invitations from existing members, outbound WOM can be precisely tracked. Along with traditional marketing, WOM can then be linked to the number of new members subsequently joining the site (sign-ups). Because of the endogeneity among WOM, new sign-ups, and traditional marketing activity, the authors employ a vector autoregressive (VAR) modeling approach. Estimates from the VAR model show that WOM referrals have substantially longer carryover effects than traditional marketing actions and produce substantially higher response elasticities. Based on revenue from advertising impressions served to a new member, the monetary value of a WOM referral can be calculated; this yields an upper-bound estimate for the financial incentives the firm might offer to stimulate WOM.
Web link: http://blog.ub.ac.id/ yuliadm/files/2012/10/Jurnal-Manajemen-Pemasaran.pdf
15) Wu, G., Sun, T., & Youn, S. (2006). Online word-of-mouth (or mouse): An exploration of its antecedents and consequences. Journal of Computer-Mediated Communication, 11(4), 1104-1127.
Abstract: This study developed an integrated model to explore the antecedents and consequences of online word-of-mouth in the context of music-related communication. Based on survey data from college students, online word-of-mouth was measured with the following two components: online opinion leadership and online opinion seeking. The results identified innovativeness, Internet usage, and Internet social connection as significant predictors of online word-of-mouth, and online forwarding and online chatting as behavioral consequences of online word-of-mouth. Contrary to the original hypothesis, music involvement was found not to be significantly related to online word-of-mouth.
Web link: http://onlinelibrary.wiley.com.ezproxy.waikato.ac.nz/doi/10.1111/j.1083-6101.2006.00310.x/full
C. Online resources
Useful - Must refer to
1) Facebook Statistics and Metrics by Continents. (n.d.). Socialbakers.com. Retrieved April 3, 2013, from
http://www.socialbakers.com/countries/continents/
2) Word of Mouth Media NZ is a national media company run by Kip Brook. Word of Mouth provides press releases for daily news media. This website specializes in writing articles for public companies, private companies, for artists, fashion, tourism, wine, events, sport, health, charity and public issues.
http://wordofmouthnz.com/
3) The Word of Mouth Marketing Association is the official trade association dedicated to word of mouth and social media marketing.
http://www.womma.org/
Useful - Must refer to
1) Cakim, I. M. (2010). Implementing word of mouth marketing: Online strategies to identify influencers, craft stories, and draw customers. Hoboken, N.J: Wiley.
Call number: HF5827.95 .C35 2010 – University of Waikato Library, Central library – Level 3
2) Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (2nd ed.). Thousand Oaks, Calif: Sage Publications.
Call number: H62 .C71 2009 – University of Waikato Library, Central library – Level 3
3) Golden, M. (2011). Social media strategies for professionals and their firms: The guide to establishing credibility and accelerating relationships. N.J.: Wiley.
Call number: HF5415.1265 .G63 2011 – University of Waikato Library, Central library – Level 3
4) Qualman, E. (2009). Socialnomics: How social media transforms the way we live and do business. Hoboken, N.J: Wiley.
Call number: HF5415.1265 Q83 2009 – University of Waikato Library, Central library – Level 3
Useful – Worth considering
1) Brown, D. (2008). Influencer marketing: Who really influences your customers? Amsterdam ; Oxford: Elsevier/Butterworth-Heinemann.
Call number: HF5414 .B76 2008 – University of Waikato Library, Central library – Level 3
2) Bryman, A., & Bell, E. (2011). Business Research Methods (3rd ed.). Oxford: Oxford University Press.
Call number: HD30.4 .B79 2011 – University of Waikato Library, Central library – Level 3
3) Sterne, J., & ebrary, Inc. (2010). Social media metrics: How to measure and optimize your marketing investment. Hoboken, N.J: Wiley.
Retrieved from http://site.ebrary.com/lib/waikato/Doc?id=10377809
Low value – Can ignore
1) Brown, R. (2009). Public relations and the social web: Using social media and Web 2.0 in communications. London ; Philadelphia: Kogan Page.
Call number: HM1221 .B76 2009 – University of Waikato Library, Central library – Level 3
2) Safko, L. (2009). The social media bible: Tactics, tools, and strategies for business success. Hoboken, N.J: John Wiley & Sons.
Call number: HF5415.1265 .S24 2009 – University of Waikato Library, Central library – Level 3
B. Articles:
Useful - Must refer to
1) Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An Elaboration Likelihood Model. MIS Quarterly, 30(4), 805–825. doi:10.2307/25148755.
Abstract: This study examines how processes of external influence shape information technology acceptance among potential users, how such influence effects vary across a user population, and whether these effects are persistent over time. Drawing on the elaboration-likelihood model (ELM), the authors compared two alternative influence processes, the central and peripheral routes, in motivating IT acceptance.
These processes were respectively operationalized using the argument quality and source credibility constructs, and linked to perceived usefulness and attitude, the core perceptual drivers of IT acceptance. This study contributes to the IT acceptance literature by introducing ELM as a referent theory for acceptance research, by elaborating alternative modes of influence, and by specifying factors moderating their effects.
Web link: http://www.jstor.org.ezproxy. waikato.ac.nz/ stable/10.2307/25148755
2) Brown, J., Broderick, A. J., & Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. Journal of interactive marketing, 21(3), 2–20.
Abstract: The authors report the results of a two-stage study aimed at investigating online WOM: a set of in-depth qualitative interviews followed by a social network analysis of a single online community. The results provide strong evidence that individuals behave as if Web sites themselves are primary “actors” in social networks and that online communities can act as a social proxy for individual identification. The authors offer a conceptualization of online social networks which takes the Web site into account as an actor,an initial exploration of the concept of a consumer–Web site relationship, and a conceptual model of the online interaction and information evaluation process.
Web link: http://www.sciencedirect.com.ezproxy.waikato.ac.nz/science/article/pii/S1094996807700300
3) Cheung, C. M. K., Lee, M. K. O., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Research, 18(3), 229–247.
Abstract: The paper examines the extent to which opinion seekers are willing to accept and adopt online consumer reviews and which factors encourage adoption. Using dual-process theories, an information adoption model was developed to examine the factors affecting information adoption of online opinion seekers. The model was tested empirically using a sample of 154 users who had experience within the online customer community, Openrice.com. Users were required to complete a survey regarding the online consumer reviews received from the virtual sharing platform.The paper found comprehensiveness and relevance to be the most effective components of the argument quality construct of the research model, making them key influencers of information adoption.
Web link:http://search.proquest.com. ezproxy.waikato.ac.nz/docview /219845247
4) Cheung, M. Y., Luo, C., Sia, C. L., & Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of online consumer recommendations. International Journal of Electronic Commerce, 13(4), 9–38. doi:10.2753/JEC1086-4415130402
Abstract:Word-of-mouth (WOM) study is extended to the on-line context (eWOM) by examining the informational and normative determinants of the perceived credibility of on-line consumer recommendations. A survey of users of an on-line consumer discussion forum in China substantiated the effects of the determinants, although post-hoc analyses revealed that prior knowledge and involvement level moderate some of them. Implications for research and practice are discussed.
Web link: http://web.ebscohost.com.ezproxy.waikato.ac.nz/ehost/detail?sid=09a81f36-790e-4d85-aa04-258fda79dc7b%40sessionmgr198&vid=1&hid=117&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=buh&AN=41423245
5) Flanagin, A. J., & Metzger, M. J. (2008). Digital media and youth: Unparalleled opportunity and unprecedented responsibility. Digital Media, Youth, and Credibility, 5–27.
Abstract:The article examines the major issues with regard to credibility and, in particular, what special concerns arise for youth populations. This volume represents a first step toward mapping that complexity and providing a basis for future work that seeks to find explanations that will ultimately help scholars, educators, policymakers, and youth take advantage of the new opportunities for empowerment and learning offered by digital networked media.
Web link: http://mitpress2.mit.edu/ books/chapters /0262562324chap1.pdf
6) Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006). E-WOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty. Journal of Business Research, 59(4), 449–456. doi:10.1016/j.jbusres.2005.10.004
Abstract: This paper investigates the effects of a specific form of electronic word-of-mouth (eWOM) communication, customer-to-customer know-how exchange, on customer perceptions of value and customer loyalty intentions. In addition, the paper explores the antecedents of customer-to-customer know-how exchange overlooked in prior research: motivation, opportunity, and ability. The survey results from 616 participants of an online forum suggest that customer know-how exchange impacts customer perceptions of product value and likelihood to recommend the product, but does not influence customer repurchase intentions. Interestingly, opportunity did not impact know-how exchange, whereas motivation and ability did have a significant effect
Web link: http://www.sciencedirect.com.ezproxy.waikato.ac.nz/science/article/pii/S0148296305001517
7) 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 Marketing, 18(1), 38–52. doi:10.1002/dir.10073
Abstract: The Internet makes it possible for consumers to obtain electronic word of mouth from other consumers. Customer comments articulated via the Internet are available to a vast number of other customers, and therefore can be expected to have a significant impact on the success of goods and services. This paper derives several motives that explain why customers retrieve other customers' on-line articulations from Web-based consumer opinion platforms. The relevance of these motives and their impact on consumer buying and communication behavior are tested in a large-scale empirical study. The results illustrate that consumers read on-line articulations mainly to save decision-making time and make better buying decisions. Structural equation modeling shows that their motives for retrieving on-line articulations strongly influence their behavior.
Web link: http://web.ebscohost.com.ezproxy.waikato.ac.nz/ehost/detail?sid=a2911a79-377c-4fe2-bebd-eb5960f8df48%40sessionmgr115&vid=1&hid=117&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=buh&AN=12302034
8) Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business horizons, 53(1), 59–68.
Abstract: The concept of Social Media is top of the agenda for many business executives today. Decision makers, as well as consultants, try to identify ways in which firms can make profitable use of applications such as Wikipedia, YouTube, Facebook, Second Life, and Twitter. Yet despite this interest, there seems to be very limited understanding of what the term “Social Media” exactly means; this article intends to provide some clarification. The authors begin by describing the concept of Social Media, and discuss how it differs from related concepts such as Web 2.0 and User Generated Content. Based on this definition, the authors then provide a classification of Social Media which groups applications currently subsumed under the generalized term into more specific categories by characteristic: collaborative projects, blogs, content communities, social networking sites, virtual game worlds, and virtual social worlds. Finally, we present 10 pieces of advice for companies which decide to utilize Social Media.
Web link: http://www.sciencedirect.com.ezproxy.waikato.ac.nz/science/article/pii/S0007681309001232
9) McKnight, H., & Kacmar, C. (2006). Factors of information credibility for an internet advice site. In System Sciences, 2006. HICSS’06. Proceedings of the 39th Annual Hawaii International Conference on (Vol. 6, p. 113b–113b). Retrieved from http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1579516
Abstract: Information credibility is important to Internet advice site vendors because they primarily build a revenue stream based on how credible consumers consider the information on the website. Unless consumers believe the website’s information is credible, they are not likely to be willing to act on the advice. This paper reports on an empirical study of how individual differences and initial site impressions affect perceptions of website information credibility. Results confirm that most of the proposed individual difference and initial impression variables play an important role in how consumers view the credibility of an unfamiliar website. Implications are included regarding adapting websites to take into account initial site impressions and individual differences.
Web link: http://ieeexplore.ieee.org /xpls /abs_all.jsp?arnumber =1579516
10) Needham, A. (2008). Word of mouth, youth and their brands. Young Consumers: Insight and Ideas for Responsible Marketers, 9(1), 60–62.
Abstract: Using Headbox, a researc and seeding community for 30,000 16-25 year olds who share their thoughts, their opinions and their ideas and get rewarded for it, consumer insights on brands and how positive and negative WOM are described. The paper finds that the importance of co-creation is vital in diffusion. Co-creation implies that marketing happens with young people rather than it being directed at them. Managerial implications suggest a new mindset toward marketing and greater emphasis on the active role of social communities in the youth market. A new approach to marketing using social networking and a very large sample suggests that we are near to a clearer understanding of the complexities of diffusion by WOM.
Web link: http://www.emeraldinsight.com.ezproxy.waikato.ac.nz/journals.htm?articleid=1714964&show=abstract
11) O’Reilly, K., & Marx, S. (2011). How young, technical consumers assess online WOM credibility. Qualitative Market Research: An International Journal, 14(4), 330–359.
Abstract: Analysis shows that participants exhibit more of a “bricks-to-clicks” than a “clicks-to-bricks” purchasing cycle. In addition to relying on customer reviews online, participants accept online WOM to enhance their self-worth, avoid risk, or enact negativity bias. Additionally, assessment of online WOM credibility is based on four factors: the polarity and quantity of posts, the logic and articulation of posts, the ability to find corroborating sources, and the previous experience of participants with particular sellers.
Web link: http://www.emeraldinsight.com.ezproxy.waikato.ac.nz/journals.htm?articleid=1950949&show=abstract
12) Racherla, P., & King, R. (2012). What we know and don’t know about online word-of-mouth: A systematic review and synthesis of the literature (SSRN Scholarly Paper No. ID 2187040). Rochester, NY: Social Science Research Network.
Abstract: Based on a systematic review of 148 studies, the authors conduct a multi-dimensional analysis of e-WOM communication, consumption and effects. Results show that the factors that drive consumers to generate/transmit e-WOM include need for self-enhancement, social interaction and altruism. These factors also assure the generation of quality information that benefits consumers who seek eWOM. The findings indicate that the effects of eWOM on consumer and market-level outcomes are not linear and vary significantly owing to eWOM dimensions such as valence and volume, and across products and consumers. With social media and other eWOM platforms taking central stage in marketing and promotional strategies, it is important to consider the key effects of eWOM on metrics such as consumer loyalty, life-time value and service delivery costs.
Web link: http://papers.ssrn.com/abstract=2187040
13) Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 14(1), 47–65. doi:10.1287/isre.14.1.47.14767
Abstract: This research investigates how knowledge workers are influenced to adopt the advice that they receive in mediated contexts. The research integrates the Technology Acceptance Model with dual-process models of informational influence. The model is investigated qualitatively first, using interviews of a sample of 40 consultants, and then quantitatively on another sample of 63 consultants from the same international consulting organization. Data reflect participants' perceptions of actual e-mails they received from colleagues consisting of advice or recommendations. Results support the model, suggesting that the process models used to understand information adoption can be generalized to the field of knowledge management, and that usefulness serves a mediating role between influence processes and information adoption. Organizational knowledge work is becoming increasingly global. This research offers a model for understanding knowledge transfer using computer-mediated communication.
Web link: http://isr.journal.informs.org.ezproxy.waikato.ac.nz/content/14/1/47.full.pdf
14) Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site. Journal of Marketing, 73(5), 90–102
Abstract: The authors study the effect of word-of-mouth (WOM) marketing on member growth at an Internet social networking site and compare it with traditional marketing vehicles. Because social network sites record the electronic invitations from existing members, outbound WOM can be precisely tracked. Along with traditional marketing, WOM can then be linked to the number of new members subsequently joining the site (sign-ups). Because of the endogeneity among WOM, new sign-ups, and traditional marketing activity, the authors employ a vector autoregressive (VAR) modeling approach. Estimates from the VAR model show that WOM referrals have substantially longer carryover effects than traditional marketing actions and produce substantially higher response elasticities. Based on revenue from advertising impressions served to a new member, the monetary value of a WOM referral can be calculated; this yields an upper-bound estimate for the financial incentives the firm might offer to stimulate WOM.
Web link: http://blog.ub.ac.id/ yuliadm/files/2012/10/Jurnal-Manajemen-Pemasaran.pdf
15) Wu, G., Sun, T., & Youn, S. (2006). Online word-of-mouth (or mouse): An exploration of its antecedents and consequences. Journal of Computer-Mediated Communication, 11(4), 1104-1127.
Abstract: This study developed an integrated model to explore the antecedents and consequences of online word-of-mouth in the context of music-related communication. Based on survey data from college students, online word-of-mouth was measured with the following two components: online opinion leadership and online opinion seeking. The results identified innovativeness, Internet usage, and Internet social connection as significant predictors of online word-of-mouth, and online forwarding and online chatting as behavioral consequences of online word-of-mouth. Contrary to the original hypothesis, music involvement was found not to be significantly related to online word-of-mouth.
Web link: http://onlinelibrary.wiley.com.ezproxy.waikato.ac.nz/doi/10.1111/j.1083-6101.2006.00310.x/full
C. Online resources
Useful - Must refer to
1) Facebook Statistics and Metrics by Continents. (n.d.). Socialbakers.com. Retrieved April 3, 2013, from
http://www.socialbakers.com/countries/continents/
2) Word of Mouth Media NZ is a national media company run by Kip Brook. Word of Mouth provides press releases for daily news media. This website specializes in writing articles for public companies, private companies, for artists, fashion, tourism, wine, events, sport, health, charity and public issues.
http://wordofmouthnz.com/
3) The Word of Mouth Marketing Association is the official trade association dedicated to word of mouth and social media marketing.
http://www.womma.org/