Confirmatory Factor Analysis of Electronic Word of Mouth of Local Coffee Shops
Main Article Content
Abstract
The purpose of this quantitative research is to analyze factors of word of mouth of local coffee shops. A structural questionnaire was applied to collect data from 250 samples by convenience sampling. Statistics used to analyze data included percentage, frequency, exploratory and confirmatory factor analysis. The findings show that electronic word of mouth of local coffee shops was composed of 6 components, including the involvement component, the source credibility component, the quality component, the sender’s expertise component, the recommendation rating component and the quantity component. The model had goodness-of-fit with the empirical data which the value of χ2 = 2.882, df =7, P-value =.896, χ2/df =.412, GFI =.996, AGFI =.989, CFI =1.000, RMSEA =.000 and RMR =.005
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References
Akyüz, A. (2013). Determinant factors influencing EWOM. Mediterranean Journal of Social
Sciences, 4(11), 159-166.
Al-Adwan, A. S., & Sammour, G. (2020). What makes consumers purchase mobile apps: Evidence
from Jordan. Journal of Theoretical and Applied Electronic Commerce Research, 16(2021),
–583.
Anastasiei, B., & Dospinescu, N. (2019). Electronic word-of-mouth for online retailers: Predictors of
volume and valence. Sustainability, 11(3), 1-18.
Angkasri, W., Erawan, T., & Khankaew, C. (2023). Phonkrathop khō̜ng kānsư̄sān pāk tō̜ pāk thāng
ʻilekthrō̜nik thī mī tō̜ khwām tangčhai sư̄ phalittaphan bamrung phiu nai prathēt Thai [The
effects of electronic word of mouth on purchase intention of skincare products in
Thailand]. Journal of Accountancy and Management, 15(1), 201-216.
Cantallops, S. A., & Salvi, F. (2014). New consumer behavior: A review of research on EWOM and
hotels. International Journal of Hospitality Management, 36, 41–51.
Chaiprasith, C. (2022). Phrưttikam phūbō̜riphōk kap khwām khāt wang tō̜ thurakit thī plīan pai nai
yuk lang khō wit [Consumer behavior with changing business expectations in the post-
COVID era]. Retrieved May 17, 2023, from https://www.pwc.com/th/en/pwc-thailand-blogs/blog-20220725.html.
Chu, S. -C., & Chen, H. T. (2019). Impact of consumers' corporate social responsibility-related
activities in social media on brand attitude, electronic word-of-mouth intention, and
purchase intention: A study of Chinese consumer behavior. Journal of Consumer
Behaviour, 18(6), 453-462.
Daolomchan, N., & Wanarat, S. (2019). Kānsư̄sān bǣp pāk tō̜ pāk thāng ʻilekthrō̜nik phān chō̜ ngō̜
thāng fē sabuk thī mī ʻitthi phon song phon tō̜ ʻakān tangčhai ʻasi nakhā rūrā khō̜ng
prachākō̜n nai khēt Krung Thēp Mahā Nakhō̜n [Electronic word-of-mouth in Facebook
influencing consumers’ intentions to buy luxury goods in the Bangkok metropolitan area].
Research and Development Journal SuanSunandha Rajabhat University, 11(2), 170-181.
Department of Provincial Administration. (2022). Chamnūan prachā chok ra [Total population].
Retrieved January 4, 2023, from https://stat.bora.dopa.go.th/new_stat/webPage/statBy
Year.php.
Doosti, S., Mohammad, R. J., Ali, A., Javad, K. P., & Parisa, M. A. (2016). Analyzing the influence of
electronic word of mouth on visit intention: The mediating role of tourists’ attitude and
city image. International Journal of Tourism Cities, 2(2), 137–148.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
George, D., & Mallery, P. (2003). SPSS for windows step by step: A simple guide and reference
0 update (4th ed.). Boston: Allyn & Bacon.
Hair, J., Anderson, R., Tatham, R., & Black, W. (1998). Multivariate data analysis (5th ed.). London:
Prentice Hall International.
Halstead, D. (2002). Negative word-of-mouth: Substitute for or supplement to consumer
complaints? Journal of Consumer Satisfaction/Dissatisfaction & Complaining Behavior, 15(2002), 1–12.
Hamdani, A., & Maulani, G. A. F. (2018). The influence of E-WOM on purchase intentions in local
culinary business sector. International Journal of Engineering and Technology(UAE), 7(2),
–250.
Ismagilova, E., Slade, E. L., Rana, N. P., & Dwivedi, Y. K. (2020). The effect of electronic word of
mouth communications on intention to buy: A meta-analysis. Information Systems
Frontiers, 22(5), 1203–1226.
Jalilvand, M. R., & Heidari, A. (2017). Comparing face-to-face and electronic word-of-mouth in
destination image formation: The case of Iran. Information Technology & People, 30(4),
–735.
Jamornman, U. (1980). Withī wikhro̜ tūaprakō̜p [Methods of factor analysis]. Bangkok: Department
of Educational Research, Faculty of Education, Chulalongkorn University.
Khongthanarat, C., & Assarut, N. (2018). Patčhai thī mī phalok ra thop tō̜ ʻakān raprū khwām nā
chư̄athư̄ khō̜ng kānsư̄sān bǣp pāk tō̜ pāk khō̜ng rā naʻā hān bon fē sabuk [Factors affecting
E-Wom credibility of restaurants on Facebook]. Songklanakarin Journal of Social Sciences
and Humanities, 23(2), 145-198.
Lo, L. W. T. (2014). An exploratory research on EWOM information seeking behavior and attitudes
in service consumption. Review of Integrative Business & Economics Research, 3(1), 172-
Lu, X., Li, Y., Zhang, W., & Rai, B. (2014). Consumer learning embedded in electronic word of
mouth. Journal of Electronic Commerce Research, 5(4), 300-316.
Park, C., Wang, Y., Yao, Y., & Kang, Y. (2011). Factors influencing EWOM effects: Using experience, credibility, and susceptibility. International Journal of Social Science and Humanity, 1(1), 74–79.
Phupanasang, G. (2022). Thurakit rā nakāfǣ rāi lek Tar naphit tonthun mai wai hǣ pit kitčhakān sō̜
won khāi yai rē ngō̜ pœ̄t sākhā ching thamlē sāfafik sūng [The 'small' coffee shop business
can't resist the cost effet, they parade closing down the business, while the big coffee shops accelerate the opening of branches. Competing for high traffic locations]. Retrieved May 17, 2023, from https://thestandard.co/coffee-shop-business/
Pimpa, P. (2018). Kānsưksā Thai nai patčhuban [Current Thai education]. Academic Journal of
Mahamakut Buddhist University Roi Et Campus, 7(1), 242–249.
Prasad, S., Gupta, I. C., & Totala, N. K. (2017). Social media usage, electronic word of mouth and
purchase-decision involvement. Asia-Pacific Journal of Business Administration, 9(2), 134–
Preecharat, A., & Chaiyasoonthorn, W. (2019). Phrưttikam kānchai bō̜rikān rā naʻā hān phān kān rī
wi wačhā kō̜ sư̄ sangkhom ʻō̜ nalai [Consumers’ behavior of using restaurants based on
social media reviews]. Journal of Administration and Management, 9(2), 209-219.
Reyes-Menendez, A., Saura, J. R., & Martinez-Navalon, J. G. (2019). The impact of E-WOM on hotels
management reputation: Exploring tripAdvisor review credibility with the ELM model. IEEE Access, 7(2019), 68868–68877.
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation
models: Tests of significance and descriptive goodness-of-fit measures. Methods of
Psychological Research, 8(2), 23-74.
Setheethorn, S. (2019). Thura kit rā nakāfǣ nai prathēt [Thai coffee shop business in Thailand].
Retrieved May 18, 2023, from http://fic.nfi.or.th/upload/market_overview/Rep_Cafe_ 15. 01.62.pdf.
Siddiqui, K. (2013). Heuristics for sample size determination in multivariate statistical techniques.
World Applied Sciences Journal, 27(2), 285-287.
Sirimongkol, T. (2022). ʻItthiphon khō̜ng phūm that bō̜rikān khō̜ ʻong rā nakāfǣ thī mai chai fǣ ron
chai thī song phon tō̜ khwāmtangčhai sadǣng phrưttikam kānchai bō̜rikān khō̜ng phūbō̜riphōk phān tūa prǣ nok lāng [The effects of servicescape in non-franchise coffee shops influencing on consumers’ behavioral intention to use services with mediator variables]. Songklanakarin Journal of Management Sciences, 39(2), 75-100.
Smart SME. (2018). Sō̜ ʻong rāidai chalīa khrūarư̄an Thai čhetsipčhet čhangwat māk nō̜i khǣ nai
mā dū kan [Let's look at the average income of Thai households in 77 provinces. Let's see
how much]. Retrieved January 4, 2023, from http://www.smartsme.co.th/content/101102.
Team. (2022). Thē ron kān dư̄m kāfǣ khō̜ng khon mi lō̜ lēn yon phūak khao dư̄m ʻarai læ dư̄m
yāngrai A day bulletin [Millennials drinking coffee trends. What and how do they drink? A
day bulletin]. Retrieved January 4, 2023, from https://adaybulletin.com/know-koffee-kult-millennial-coffee-trends/62882.
Tuenweeradet, K. (2018). ʻItthiphon khō̜ng kānsư̄sān kāntalāt bǣp pāk tō̜ pāk bon sư̄ ʻō̜ nalaitō̜
ʻakān tatsin čhai chai bō̜rikān rā nakāfǣ sot khō̜ng phūbō̜riphōk nai khēt Krung Thēp Mahā Nakhō̜n [Word of mouth marketing on social media towards coffee shop consumers in Bangkok] (Master’s thesis, Bangkok University).
Thanvisitthpon, N. (2021). Statistically validated component- and indicator-level requirements for sustainable Thai homestay businesses. Sustainability, 13(2), 1-17.
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),
–504.
Zhao, X., Wang, L., Guo, X., & Law, R. (2015). The influence of online reviews to online hotel
booking intentions. International Journal of Contemporary Hospitality Management, 27(6), 1343–1364.