E-WOM and consumers’ purchase intention: An empirical study on Facebook
-
DOIhttp://dx.doi.org/10.21511/im.18(3).2022.13
-
Article InfoVolume 18 2022, Issue #3, pp. 149-158
- Cited by
- 871 Views
-
426 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
Nowadays, organizations use social media to promote their services and products. At the same time, they use different tools to convey their messages, such as Facebook. Therefore, this study aims to investigate the factors that affect the e-WOM on Jordanian consumers’ purchase intention over Facebook. The study uses the information acceptance model (IAM) to examine the impact of information credibility, information quality, information adoption, and information usefulness over Facebook on Jordanian consumers’ purchase intention. The study uses cross-sectional quantitative research and is conducted online. The questionnaire was distributed through Facebook and WhatsApp, and the people who used only Facebook were allowed to complete the survey. Out of 327 filled questionnaires, only 304 were valid for further analysis. Collected data were coded in SPSS, and after confirming the validity and reliability of the tool, the correlation between variables was checked. In addition, multiple regressions were used to test the hypotheses. Multiple regression results show that the E-WOM can explain 49.2% of the total variation in the consumers’ purchase intention, where R2 = 0.492. Information adoption has the strongest effect on consumers’ purchase intention (β = 0.489), followed by information usefulness (β = 0.204). In contrast, information credibility and information quality do not have a significant effect on customers’ purchase intention (0.189 and 0.312, respectively). This study helps companies and businesses that have pages on Facebook to understand how consumers engage in the e-WOM on business pages and consider the consumers’ reviews, comments, or posts.
- Keywords
-
JEL Classification (Paper profile tab)M31, L15, L86, D83
-
References54
-
Tables5
-
Figures1
-
- Figure 1. Research model
-
- Table 1. Demographic analysis
- Table 2. Descriptive statistics and reliability test
- Table 3. Correlations
- Table 4. Model summary (ANOVA)
- Table 5. Coefficients
-
- Abedi, E., Ghorbanzadeh, D., & Rahehagh, A. (2020). Influence of eWOM information on consumers’ behavioral intentions in mobile social networks: Evidence of Iran. Journal of Advances in Management Research, 17(1), 84-109.
- Al Khasawneh, M., & Shuhaiber, A. (2013). A Comprehensive Model of Factors Influencing Consumer Attitude Towards and Acceptance of SMS Advertising: An Empirical Investigation in Jordan. International Journal of Sales and Marketing Management Research and Development, 3(2), 1-22.
- Alnsour, M. (2018). Social Media Effect on Purchase Intention: Jordanian Airline Industry. Journal of Internet Banking and Commerce, 23(2), 1-1.
- Al-Shibly, M. S., & Mahadin, B. K. (2017). The Influence of eWOM on Facebook on the Jordanian Consumers’ Intentions Towards Restaurants. International Journal of Applied Business and Economic Research, 15(22(part-III)), 67-85.
- Bailey, J. E., & Pearson, S. W. (1983). Development of a Tool for Measuring and Analyzing Computer User Satisfaction. Management Science, 29(5), 530-545.
- Bataineh, A. Q. (2015). The Impact of Perceived e-WOM on Purchase Intention: The Mediating Role of Corporate Image. International Journal of Marketing Studies, 7(1), 126-137.
- Bickart, B., & Schindler, R. M. (2001). Internet Forums As Influential. Journal of Interactive Marketing, 15(3), 31-40.
- Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185-216.
- Chan, Y. Y. Y., & Ngai, E. W. T. (2011). Conceptualising electronic word of mouth activity: An input-process-output perspective. Marketing Intelligence & Planning, 29(5), 488-516.
- Cheng, X., & Zhou, M. (2010). Empirical study on credibility of electronic word of mouth. 2010 International Conference on Management and Service Science, MASS 2010.
- Cheung, C., & Thadani, D. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), 461-470.
- Cheung, C., Lee, M., & 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.
- Cheung, R. (2014). The Influence of Electronic Word-of-Mouth on Information Adoption in Online Customer Communities. Global Economic Review, 43(1), 42-57.
- Elhadidy, D. Y. (2017). To investigate how e-WOM affects young buyers purchasing decision in FMCGS. The Business and Management Review, 8(5), 252-257.
- Erkan, I. (2016). The Impacts of Electronic Word of Mouth in Social Media on Consumer’s Purchase Intentions. International Conference on Digital Marketing.
- Erkan, I., & Evan, Ch. (2016). The Influence of Electronic Word of Mouth in Social Media on Consumers’ Purchase Intentions: An extended approach to information adoption. Computers in Human Behavior, 61, 47-55.
- Etikan, I., & Bala, K. (2017). Sampling and sampling methods. Biometrics & Biostatistics International Journal. Biometrics & Biostatistics International Journal, 5(6), 215-217.
- Facebook. (2021). Facebook Reports Fourth Quarter and Full Year 2020 Results. Investor.Fb.Com.
- Filieri, R., & McLeay, F. (2014). E-WOM and Accommodation: An Analysis of the Factors That Influence Travelers’ Adoption of Information from Online Reviews. Journal of Travel Research, 53(1), 44-57.
- Finstad, K. (2010). Response interpolation and scale sensitivity: evidence against 5-point scales. Journal of User Experience, 5(3), 104-110.
- Floyd, K., Freling, R., Alhoqail, S., Cho, H. Y., & Freling, T. (2014). How online product reviews affect retail sales: A meta-analysis. Journal of Retailing, 90(2), 217-232.
- Forman, C., Ghose, A., & Wiesenfeld, B. (2008). Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 19(3), 291-313.
- Fornell, C., & Larcker, D. F. (1981). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Journal of Marketing Research, 18(3), 382-388.
- Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis: A Global Perspective (7th ed.). Upper Saddle River: Pearson Education.
- 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.
- Hill, R. (1998). What sample size is “enough” in internet survey research? Interpersonal Computing and Technology: An Electronic Journal for the 21st Century, 6(3-4), 1-12.
- Jalilvand, M. R., & Samiei, N. (2012). The effect of electronic word of mouth on brand image and purchase intention: An empirical study in the automobile industry in Iran. Marketing Intelligence & Planning, 30(4), 460-476.
- Lee, E. J., & Shin, S. Y. (2014). When do consumers buy online product reviews? Effects of review quality, product type, and reviewer’s photo. Computers in Human Behavior, 31(1), 356-366.
- Lee, K. T., & Koo, D. M. (2015). Evaluating right versus just evaluating online consumer reviews. Computers in Human Behavior, 45, 316-327.
- Le-Hoang, P. V. (2020). The effects of Electronic Word of Mouth (eWOM) on the adoption of consumer eWOM information. Independent Journal of Management & Production, 11(6), 1760.
- Li, B., Zhu, M., Jiang, Y., & Li, Z. (2016). Pricing policies of a competitive dual-channel green supply chain. Journal of Cleaner Production, 112, 2029-2042.
- Liu, R. R., & Zhang, W. (2010). Informational influence of online customer feedback: An empirical study. Journal of Database Marketing and Customer Strategy Management, 17(2), 120-131.
- Mehyar, H., Saeed, M., Baroom, H., Afreh, A. L. I. A., & Al-adaileh, R. (2020). The impact of electronic word of mouth on consumers purchasing intention. Journal of Theoretical and Applied Information Technology, 98(02), 183-193.
- Park, D. H., & Lee, J. (2008). eWOM overload and its effect on consumer behavioral intention depending on consumer involvement. Electronic Commerce Research and Applications, 7(4), 386-398.
- Prendergast, G., Ko, D., & Yuen, S. Y. V. (2010). Online word of mouth and consumer purchase intentions. International Journal of Advertising, 29(5), 687-708.
- Rahman, A., & Rahman, M. M. (2020). Online Shopping in Bangladesh: Exploring the Factors Influencing Customers’ Decision During the Coronavirus Outbreak. China-USA Business Review, 19(3), 91-101.
- Saleem, A., & Ellahi, A. A. (2017). Influence of electronic word of mouth on purchase intention of fashion products in social networking websites. Pakistan Journal of Commerce and Social Sciences, 11(2), 597-622.
- Sedgwick, P. (2015). Confidence intervals, P values, and statistical significance. BMJ, 350.
- See-To, E. W. K., & Ho, K. K. W. (2014). Value co-creation and purchase intention in social network sites: The role of electronic Word-of-Mouth and trust – A theoretical analysis. Computers in Human Behavior, 31(1), 182-189.
- StatCounter. (n.d.). Social Media Stats Jordan. July 2021-July 2022.
- Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 14(1), 47-65.
- Sutanto, M. A., & Aprianingsih, A. (2016). The Effect of Online Consumer Review Toward Purchase Intention: A Study in Premiumcosmetic in Indonesia. International Conference on Ethics OfBusiness, Economics, and Social Science, 53(2), 1689-1699.
- Sweeney, J. C., Soutar, G. N., & Mazzarol, T. (2012). Word of mouth: Measuring the power of individual messages. European Journal of Marketing, 46(1/2), 237-257.
- Thomas, M. J., Wirtz, B. W., & Weyerer, J. C. (2019). Determinants of online review credibility and its impact on consumers’ purchase intention. Journal of Electronic Commerce Research, 20(1), 1-20.
- Tien, D. H., Amaya Rivas, A. A., & Liao, Y. K. (2019). Examining the influence of customer-to-customer electronic word-of-mouth on purchase intention in social networking sites. Asia Pacific Management Review, 24(3), 238-249.
- Troise, C., O’Driscoll, A., Tani, M., & Prisco, A. (2021). Online food delivery services and behavioural intention – a test of an integrated TAM and TPB framework. British Food Journal, 123(2), 664-683.
- Watts, S., & Wyner, G. (2011). Designing and theorizing the adoption of mobile technology-mediated ethical consumption tools. Information Technology and People, 24(3), 257-280.
- Wen, B. L. J., & Aun, N. B. (2020). Factors influencing consumers’ purchase intention in Klang Valley, Malaysia: a study of bubble milk tea. BERJAYA Journal of Services & Management, 13, 29-43.
- Yeap, J. A. L., Ignatius, J., & Ramayah, T. (2014). Determining consumers’ most preferred eWOM platform for movie reviews: A fuzzy analytic hierarchy process approach. Computers in Human Behavior, 31(1), 250-258.
- Yee, P. J. (2016). Consumers’ acceptance towards e-grocery. Applied Microbiology and Biotechnology, 85(1), 2071-2079.
- Yusuf, A. S., Che Hussin, A. R., & Busalim, A. H. (2018). Influence of e-WOM engagement on consumer purchase intention in social commerce. Journal of Services Marketing, 32(4), 493-504.
- Zeng, C. F., & Seock, Y. K. (2019). Chinese consumers’ perceptions toward social media platform for shopping and eWOM intention: a study of WeChat. International Journal of Fashion Design, Technology and Education, 12(2), 199-207.
- Zhang, J., Craciun, G., & Shin, D. (2010). When does electronic word-of-mouth matter? A study of consumer product reviews. Journal of Business Research, 63(12), 1336-1341.
- Zhang, K., Zhao, S., Cheung, C., & Lee, M. (2014). Examining the influence of online reviews on consumers’ decision-making: A heuristic-systematic model. Decision Support Systems, 67, 78-89.