Logo PTI Logo FedCSIS

Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS)

Annals of Computer Science and Information Systems, Volume 39

Mixed-Methods Study of Arabic Online Review Influence on Purchase Intention (AOCR-PI)

, ,

DOI: http://dx.doi.org/10.15439/2024F3381

Citation: Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS), M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 39, pages 6373 ()

Full text

Abstract. Online customer reviews (OCRs) have become vital for shoppers, aiding their purchase decisions amidst the rapid growth of user-generated content. However, a lack of research has been done to study the impact of OCRs on the purchase intentions of Arab consumers. Therefore, applying Western online review systems to other cultures without further consideration may pose challenges. This study aims to examine how various factors of OCRs affect Arab consumers' buying intentions. Employing a mixed-methods approach, quantitative data from a survey questionnaire (633 responses) and qualitative insights from interviews (15 participants) were collected and analysed sequentially. The findings reveal that review central cues (valence, comprehensiveness, readability and images) and some peripheral cues (volume and reviewer experience) significantly influence purchase intention. By contrast, reviewer identity disclosure and reputation are not deemed important by Arab book shoppers. The semi-structured interviews validated the significance of reading OCRs before purchase, offered insights into the impact of various related factors and revealed a new factor that is shared perspectives between the reviewer and OCR receiver. The study contributes theoretical insights and provides managerial implications for ORP developers and book publishers, aiming to enhance user experience and drive sales.

References

  1. “Survey: The Ever-Growing Power of Reviews (2023 Edition).” Accessed: May 06, 2024. [Online]. Available: https://www.powerreviews.com/power-of-reviews-2023/
  2. X. Li, C. Wu, and F. Mai, “The effect of online reviews on product sales: A joint sentiment-topic analysis,” Information and Management, vol. 56, no. 2, pp. 172–184, 2019, http://dx.doi.org/10.1016/j.im.2018.04.007.
  3. S. M. Mudambi and D. Schuff, “What makes a helpful review? A study of customer reviews on amazon.com,” MIS Quarterly, vol. 34, no. 1, pp. 185–200, 2010, http://dx.doi.org/10.1016/j.ica.2011.08.067.
  4. H. Hong, D. Xu, G. A. Wang, and W. Fan, “Understanding the determinants of online review helpfulness: A meta-analytic investigation,” Decision Support Systems, vol. 102, pp. 1–11, 2017, http://dx.doi.org/10.1016/j.dss.2017.06.007.
  5. B. Gu, J. Park, and P. Konana, “The impact of external word-of-mouth sources on retailer sales of high-involvement products,” Information Systems Research, vol. 23, no. 1, pp. 182–196, 2012, http://dx.doi.org/10.1287/isre.1100.0343.
  6. C. Luo, J. Wu, Y. Shi, and Y. Xu, “The effects of individualism–collectivism cultural orientation on eWOM information,” International Journal of Information Management, vol. 34, pp. 446–456, 2014, http://dx.doi.org/10.1016/j.ijinfomgt.2014.04.001.
  7. J. E. M. Steenkamp and I. Geyskens, “How Country Characteristics Affect the Perceived Value of Web Sites,” Journal of Marketing, vol. 70, no. 3, pp. 136–150, 2006, http://dx.doi.org/10.1509/jmkg.70.3.136.
  8. R. E. Petty and J. T. Cacioppo, “The elaboration likelihood model of persuasion,” in Advances in Experimental Social Psychology, vol. 19, no. C, 1986, pp. 123–205. http://dx.doi.org/10.1016/S0065-2601(08)60214-2.
  9. E. T. Hall, Beyond culture. Garden City, N.Y.: Anchor Press, 1976. http://dx.doi.org/10.4324/9780203894880.ch3.
  10. G. Hofstede, “Culture and Organizations,” International Studies of Management & Organization, vol. 10, no. 4, pp. 15–41, Dec. 1980, http://dx.doi.org/10.1080/00208825.1980.11656300.
  11. A. Alghamdi, N. Beloff, and M. White, “A New Arabic Online Consumer Reviews Model to Aid Purchasing Intention (AOCR-PI),” in Lecture Notes in Networks and Systems, K. (eds) I. S. and Applications. I. 2022 Arai, Ed., Cham: Springer, 2023, pp. 475–492. http://dx.doi.org/10.1007/978-3-031-16072-1_35.
  12. W. Kai, L. Xiaojuan, and H. Yutong, “Exploring Goodreads reviews for book impact assessment,” Journal of Informetrics, vol. 13, pp. 874–886, 2019, http://dx.doi.org/10.1016/j.joi.2019.07.003.
  13. R. E. Petty, J. T. Cacioppo, A. J. Strathman, and J. R. Priester, “To think or not to think. Exploring two routes to persuasion,” in Persuasion: Psychological insights and perspectives, 2005, pp. 81–116.
  14. J. W. Creswell and V. L. P. Clark, Designing and Conducting Mixed Methods Research, 3rd ed., no. 1. Thousand Oaks, California: SAGE Publications, Inc, 2018. http://dx.doi.org/10.1177/1937586719832223.
  15. J. Berger, “Word of mouth and interpersonal communication: A review and directions for future research,” Journal of Consumer Psychology, vol. 24, no. 4, pp. 586–607, 2014, http://dx.doi.org/10.1016/j.jcps.2014.05.002.
  16. J. F. Hair, J. J. Risher, and C. M. Ringle, “When to use and how to report the results of PLS-SEM,” vol. 31, no. 1, pp. 2–24, 2019, http://dx.doi.org/10.1108/EBR-11-2018-0203.
  17. M. N. K. Saunders, P. Lewis, and A. Thornhill, Research methods for business students, 6th ed. Harlow, England ; New York: Pearson, 2012.
  18. D. Silverman, Doing Qualitative Research, 5th ed. London: SAGE Publications Ltd, 2017.
  19. V. Braun and V. Clarke, “Using thematic analysis in psychology,” Qualitative Research in Psychology, vol. 3, no. 2, pp. 77–101, 2006, http://dx.doi.org/10.1191/1478088706qp063oa.
  20. “goodreads.com Traffic Analytics, Ranking & Audience [March 2024],” Similarweb. Accessed: May 06, 2024. [Online]. Available: https://www.similarweb.com/website/goodreads.com/
  21. P. M. Podsakoff, S. B. MacKenzie, J. Y. Lee, and N. P. Podsakoff, “Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies,” Journal of Applied Psychology, vol. 88, no. 5, pp. 879–903, 2003, http://dx.doi.org/10.1037/0021-9010.88.5.879.
  22. A. Sharma, Y. K. Dwivedi, V. Arya, and M. Q. Siddiqui, “Does SMS advertising still have relevance to increase consumer purchase intention? A hybrid PLS-SEM-neural network modelling approach,” Computers in Human Behavior, vol. 124, no. January, p. 106919, 2021, http://dx.doi.org/10.1016/j.chb.2021.106919.
  23. Z. Sheikh, T. Islam, S. Rana, Z. Hameed, and U. Saeed, “Acceptance of social commerce framework in Saudi Arabia,” Telematics and Informatics, vol. 34, no. 8, pp. 1693–1708, 2017, http://dx.doi.org/10.1016/j.tele.2017.08.003.
  24. J. Hair Jr, G. Hult, C. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2017.
  25. J. Henseler, C. M. Ringle, and R. R. Sinkovics, “The use of partial least squares path modeling in international marketing,” Advances in International Marketing, vol. 20, pp. 277–319, 2009, http://dx.doi.org/10.1108/S1474-7979(2009)0000020014.
  26. C. Fornell and D. F. Larcker, “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing Research, vol. 18, no. 1, p. 39, Feb. 1981, http://dx.doi.org/10.2307/3151312.
  27. J. Henseler, C. M. Ringle, and M. Sarstedt, “A new criterion for assessing discriminant validity in variance-based structural equation modeling,” Journal of the Academy of Marketing Science, vol. 43, no. 1, pp. 115–135, 2015, http://dx.doi.org/10.1007/s11747-014-0403-8.
  28. A. Shukla and A. Mishra, “Role of Review Length, Review Valence and Review Credibility on Consumer’s Online Hotel Booking Intention,” FIIB Business Review, vol. 12, no. 4, pp. 403–414, 2022, http://dx.doi.org/10.1177/23197145221099683.
  29. A. Shukla and A. Mishra, “Effects of Visual Information and Argument Concreteness on Purchase Intention of Consumers Towards Online Hotel Booking,” Vision, vol. 27, no. 5, pp. 639–649, 2021, http://dx.doi.org/10.1177/09722629211038069.
  30. R. A. L. Fischer, R. Walczuch, and E. Guzman, “Does Culture Matter? Impact of Individualism and Uncertainty Avoidance on App Reviews,” 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS), pp. 67–76, 2021, http://dx.doi.org/10.1109/ICSE-SEIS52602.2021.00016.
  31. M. R. González-Rodríguez, M. C. Díaz-Fernández, A. Bilgihan, F. Okumus, and F. Shi, “The impact of eWOM source credibility on destination visit intention and online involvement: a case of Chinese tourists,” Journal of Hospitality and Tourism Technology, vol. 13, no. 5, pp. 855–874, 2022, http://dx.doi.org/10.1108/JHTT-11-2021-0321.
  32. A. ur Rehman, “Consumers’ perceived value of luxury goods through the lens of Hofstede cultural dimensions: A cross-cultural study,” Journal of Public Affairs, vol. 22, no. 4, 2021, http://dx.doi.org/10.1002/pa.2660.
  33. Y. Li, X. Wang, and C. Van Slyke, “Determinants of online professor reviews: an elaboration likelihood model perspective,” Internet Research, 2022, http://dx.doi.org/10.1108/INTR-11-2020-0627.
  34. S. G. Moore and K. C. Lafreniere, “How online word‐of‐mouth impacts receivers,” Consumer Psychology Review, vol. 3, no. 1, pp. 34–59, 2020, http://dx.doi.org/10.1002/arcp.1055.
  35. S. Teng, K. W. Khong, A. Y. L. Chong, and B. Lin, “Examining the impacts of electronic word-of-mouth message on consumers’ attitude,” Journal of Computer Information Systems, vol. 57, no. 3, pp. 238–251, 2017, http://dx.doi.org/10.1080/08874417.2016.1184012.
  36. J. W. Cheong, S. Muthaly, M. Kuppusamy, and C. Han, “The study of online reviews and its relationship to online purchase intention for electronic products among the millennials in Malaysia,” Asia Pacific Journal of Marketing and Logistics, vol. 32, no. 7, pp. 1519–1538, 2020, http://dx.doi.org/10.1108/APJML-03-2019-0192.
  37. E. Ismagilova, E. L. Slade, N. P. Rana, and Y. K. Dwivedi, “The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis,” Information Systems Frontiers, vol. 22, no. 5, pp. 1203–1226, 2019, http://dx.doi.org/10.1007/s10796-019-09924-y.
  38. M. A. Sutanto and A. Aprianingsih, “the Effect of Online Consumer Review Toward Purchase Intention: a Study in Premium Cosmetic in Indonesia,” International Conference on Ethics of Business, Economics, and Social Science, pp. 218–230, 2016.
  39. G. Hofstede, “Dimensionalizing Cultures: The Hofstede Model in Context,” Online Readings in Psychology and Culture, vol. 2, no. 1, pp. 2307–0919, 2011, http://dx.doi.org/10.9707/2307-0919.1014.
  40. J. Li and L. Zhan, “How the written word drives WOM: Evidence from consumer-generated product reviews,” Journal of Advertising Research, vol. 51, no. 1, pp. 239–257, 2011, http://dx.doi.org/10.2501/JAR-51-1-239-257.
  41. L. V. Casaló, C. Flavián, M. Guinalíu, and Y. Ekinci, “Avoiding the dark side of positive online consumer reviews: Enhancing reviews’ usefulness for high risk-averse travelers,” Journal of Business Research, vol. 68, no. 9, pp. 1829–1835, 2015, http://dx.doi.org/10.1016/j.jbusres.2015.01.010.
  42. K. Z. K. Zhang, S. J. Zhao, C. M. K. Cheung, and M. K. O. Lee, “Examining the influence of online reviews on consumers’ decision-making: A heuristic-systematic model,” Decision Support Systems, vol. 67, pp. 78–89, 2014, http://dx.doi.org/10.1016/j.dss.2014.08.005.
  43. K. L. Xie, Z. Zhang, and Z. Zhang, “The business value of online consumer reviews and management response to hotel performance,” International Journal of Hospitality Management, vol. 43, pp. 1–12, 2014, http://dx.doi.org/10.1016/j.ijhm.2014.07.007.
  44. D. J. Bosman, C. Boshoff, and G.-J. Van Rooyen, “The review credibility of electronic word-of-mouth communication on e-commerce platforms,” Management Dynamics, vol. 22, no. 3, pp. 29–44, 2013.
  45. G. Hofstede, G. J. Hofstede, and M. Minkov, Cultures and organizations: software of the mind: intercultural cooperation and its importance for survival, vol. 17, no. 4. New York: McGraw-Hil, 2010. http://dx.doi.org/10.1177/030630709201700409.
  46. Z. Zhao, J. Wang, H. Sun, Y. Liu, Z. Fan, and F. Xuan, “What Factors Influence Online Product Sales? Online Reviews, Review System Curation, Online Promotional Marketing and Seller Guarantees Analysis,” IEEE Access, vol. 8, pp. 3920–3931, 2020, http://dx.doi.org/10.1109/ACCESS.2019.2963047.
  47. Y. H. Cheng and H. Y. Ho, “Social influence’s impact on reader perceptions of online reviews,” Journal of Business Research, vol. 68, no. 4, pp. 883–887, 2015, http://dx.doi.org/10.1016/j.jbusres.2014.11.046.
  48. R. Filieri, Z. Lin, G. Pino, S. Alguezaui, and A. Inversini, “The role of visual cues in eWOM on consumers’ behavioral intention and decisions,” Journal of Business Research, vol. 135, no. June, pp. 663–675, 2021, http://dx.doi.org/10.1016/j.jbusres.2021.06.055.
  49. T. Y. Wang and J. Park, “Destination Information Search in Social Media and Travel Intention of Generation Z University Students,” Journal of China Tourism Research, vol. 19, no. 3, pp. 570–588, 2023, http://dx.doi.org/10.1080/19388160.2022.2101574.
  50. B. Fang, Q. Ye, D. Kucukusta, and R. Law, “Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics,” Tourism Management, vol. 52, pp. 498–506, 2016, http://dx.doi.org/10.1016/j.tourman.2015.07.018.
  51. A. Agnihotri and S. Bhattacharya, “Online Review Helpfulness: Role of Qualitative Factors,” Psychology & Marketing, vol. 33, no. 11, pp. 1006–1017, 2016, http://dx.doi.org/10.1002/mar.
  52. I. Syafganti and M. Walrave, “Assessing the Effects of Valence and Reviewers’ Expertise on Consumers’ Intention to Book and Recommend a Hotel,” International Journal of Hospitality and Tourism Administration, vol. 23, no. 5, pp. 904–923, 2022, http://dx.doi.org/10.1080/15256480.2021.1881939.
  53. B. Lis, “In eWOM We Trust: A Framework of Factors that Determine the eWOM Credibility,” Bus Inf Syst Eng, vol. 5, no. 3, pp. 129–140, Jun. 2013, http://dx.doi.org/10.1007/s12599-013-0261-9.
  54. H. Baek, J. Ahn, and Y. Choi, “Helpfulness of online consumer reviews: Readers’ objectives and review cues,” International Journal of Electronic Commerce, vol. 17, no. 2, pp. 99–126, 2012, http://dx.doi.org/10.2753/JEC1086-4415170204.
  55. S. R. Hill, I. Troshani, and D. Chandrasekar, “Signalling Effects of Vlogger Popularity on Online Consumers,” Journal of Computer Information Systems, vol. 60, no. 1, pp. 76–84, Jan. 2020, http://dx.doi.org/10.1080/08874417.2017.1400929.
  56. J. Li and X. Liang, “Reviewers’ Identity Cues in Online Product Reviews and Consumers’ Purchase Intention,” Frontiers in Psychology, vol. 12, Jan. 2022, http://dx.doi.org/10.3389/fpsyg.2021.784173.
  57. R. W. Naylor, C. P. Lamberton, and D. A. Norton, “Seeing Ourselves in Others: Reviewer Ambiguity, Egocentric Anchoring, and Persuasion,” Journal of Marketing Research, vol. 48, no. 3, pp. 617–631, 2011, http://dx.doi.org/10.1509/jmkr.48.3.617.
  58. E. Ismagilova, E. Slade, N. P. Rana, and Y. K. Dwivedi, “The effect of characteristics of source credibility on consumer behaviour: A meta-analysis,” Journal of Retailing and Consumer Services, vol. 53, p. 101736, Mar. 2020, http://dx.doi.org/10.1016/j.jretconser.2019.01.005.
  59. H. J. Cheong and S. Mohammed-Baksh, “U.S. and Korean Consumers: A Cross-Cultural Examination of Product Information-Seeking and -Giving,” Journal of Promotion Management, vol. 26, no. 6, pp. 893–910, 2020, http://dx.doi.org/10.1080/10496491.2020.1745985.
  60. G. Roy, B. Datta, and R. Basu, “Effect of eWOM Valence on Online Retail Sales,” Global Business Review, vol. 18, no. 1, pp. 198–209, 2017, http://dx.doi.org/10.1177/0972150916666966.
  61. E. T. Hall and M. R. Hall, Understanding cultural differences. Yarmouth, ME: Intercultural Press, 1990. http://dx.doi.org/10.4324/9781315277349-2.
  62. Z. Zhu, J. Liu, and W. Dong, “Factors correlated with the perceived usefulness of online reviews for consumers: a meta-analysis of the moderating effects of product type,” AJIM, vol. 74, no. 2, pp. 265–288, Feb. 2022, http://dx.doi.org/10.1108/AJIM-02-2021-0054.
  63. R. Zinko, P. Stolk, Z. Furner, and B. Almond, “A picture is worth a thousand words: how images influence information quality and information load in online reviews,” Electronic Markets, vol. 30, no. 4, pp. 775–789, 2020, http://dx.doi.org/10.1007/s12525-019-00345-y.
  64. M. Walsh and M. Antoniak, “The goodreads ‘classics’: A computational study of readers, amazon, and crowdsourced amateur criticism,” Journal of Cultural Analytics, vol. 4, no. 1, pp. 243–287, 2021, http://dx.doi.org/10.22148/001C.22221.