Determinants of Customers' Purchasing Intention of Fresh Agricultural Products: SEM Analysis
Downloads
With the ongoing advancement and widespread use of internet technologies, e-commerce has become a dominant retail channel, and the emergence of live-streaming platforms now offers companies a dynamic new way to market and sell products. Nevertheless, this business model also heightens the issue of information asymmetry, as consumers often face challenges in accurately assessing product quality and determining the credibility of sellers, making the enhancement of consumer trust a key concern for e-commerce enterprises. This study examines how information acquisition ability and online word of mouth regarding fresh agricultural products on Chinese live-streaming platforms influence consumers’ purchase intentions, with a particular focus on the mediating role of perceived value. Analysis of 372 valid survey responses reveals that both information acquisition ability and online word of mouth significantly increase purchase intentions, and that perceived value acts as a critical mechanism linking these factors. The findings also indicate the importance of real-time interaction in boosting sales and fostering deeper consumer engagement. Based on these insights, the study recommends strengthening consumers’ ability to access and evaluate product information, cultivating credible and positive online word of mouth, and leveraging interactive live-streaming features to enhance product displays and review systems. These contributions advance theoretical understanding of consumer behavior in digital marketing contexts and provide practical guidance for enterprises seeking to improve their live-streaming e-commerce strategies.
Downloads
[1] Sun, Y., Shao, X., Li, X., Guo, Y., & Nie, K. (2019). How live streaming influences purchase intentions in social commerce: An IT affordance perspective. Electronic Commerce Research and Applications, 37. doi:10.1016/j.elerap.2019.100886.
[2] Zhang, M., Qin, F., Wang, G. A., & Luo, C. (2019). The impact of live video streaming on online purchase intention. The Service Industries Journal, 40(9-10), 656–681. doi:10.1080/02642069.2019.1576642.
[3] Liu, C., Li, J., Steele, W., & Fang, X. (2018). A study on Chinese consumer preferences for food traceability information using best-worst scaling. PLoS ONE, 13(11), 206793. doi:10.1371/journal.pone.0206793.
[4] Lim, X. J., Cheah, J. H., Waller, D. S., Ting, H., & Ng, S. I. (2020). What s-commerce implies? Repurchase intention and its antecedents. Marketing Intelligence and Planning, 38(6), 760–776. doi:10.1108/MIP-03-2019-0145.
[5] Hu, M., & Chaudhry, S. S. (2020). Enhancing consumer engagement in e-commerce live streaming via relational bonds. Internet Research, 30(3), 1019–1041. doi:10.1108/INTR-03-2019-0082.
[6] Wongkitrungrueng, A., & Assarut, N. (2020). The role of live streaming in building consumer trust and engagement with social commerce sellers. Journal of Business Research, 117, 543–556. doi:10.1016/j.jbusres.2018.08.032.
[7] Cheung, C. M. K., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), 461–470. doi:10.1016/j.dss.2012.06.008.
[8] Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203–220. doi:10.1016/S0022-4359(01)00041-0.
[9] Acemoglu, D., & Autor, D. (2011). Skills, Tasks and Technologies: Implications for Employment and Earnings. Handbook of Labor Economics, Elsevier, Amsterdam, Netherlands. doi:10.1016/S0169-7218(11)02410-5.
[10] Deichmann, U., Goyal, A., & Mishra, D. (2016). Will digital technologies transform agriculture in developing countries? Agricultural Economics (United Kingdom), 47(S1), 21–33. doi:10.1111/agec.12300.
[11] Klerkx, L., Jakku, E., & Labarthe, P. (2019). A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda. NJAS - Wageningen Journal of Life Sciences, 90–91, 100315. doi:10.1016/j.njas.2019.100315.
[12] Simon, H. A. (1979). Information Processing Models of Cognition. Annual Review of Psychology, 30(1), 363–396. doi:10.1146/annurev.ps.30.020179.002051.
[13] Bettman, J. R., Luce, M. F., & Payne, J. W. (1998). Constructive consumer choice processes. Journal of Consumer Research, 25(3), 187–217. doi:10.1086/209535.
[14] Alba, J. W., & Hutchinson, J. W. (1987). Dimensions of Consumer Expertise. Journal of Consumer Research, 13(4), 411. doi:10.1086/209080.
[15] 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.
[16] Mudambi, S. M., & Schuff, D. (2010). What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.Com1. MIS Quarterly, 34(1), 185–200. doi:10.2307/20721420.
[17] Liu, Y. (2006). Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue. Journal of Marketing, 70(3), 74–89. doi:10.1509/jmkg.70.3.074.
[18] Berger, J., Sorensen, A. T., & Rasmussen, S. J. (2010). Positive effects of negative publicity: When negative reviews increase sales. Marketing Science, 29(5), 815–827. doi:10.1287/mksc.1090.0557.
[19] Dellarocas, C., Zhang, X., & Awad, N. F. (2007). Exploring the value of online product reviews in forecasting sales: The case of motion pictures. Journal of Interactive Marketing, 21(4), 23–45. doi:10.1002/dir.20087.
[20] Filieri, R., Alguezaui, S., & McLeay, F. (2015). Why do travelers trust TripAdvisor? Antecedents of trust towards consumer-generated media and its influence on recommendation adoption and word of mouth. Tourism Management, 51, 174–185. doi:10.1016/j.tourman.2015.05.007.
[21] Zeithaml, V. A. (1988). Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52(3), 2–22. doi:10.1177/002224298805200302.
[22] Sheth, J. N., Newman, B. I., & Gross, B. L. (1991). Why we buy what we buy: A theory of consumption values. Journal of Business Research, 22(2), 159–170. doi:10.1016/0148-2963(91)90050-8.
[23] Fernqvist, F., & Ekelund, L. (2014). Credence and the effect on consumer liking of food - A review. Food Quality and Preference, 32, 340–353. doi:10.1016/j.foodqual.2013.10.005.
[24] Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101–134. doi:10.1080/10864415.2003.11044275.
[25] Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in Online Shopping: An Integrated Model1. MIS Quarterly, 27(1), 51–90. doi:10.2307/30036519.
[26] Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of Price, Brand, and Store Information on Buyers’ Product Evaluations. Journal of Marketing Research, 28(3), 307–319. doi:10.1177/002224379102800305.
[27] Hill, R. J., Fishbein, M., & Ajzen, I. (1977). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Contemporary Sociology, 6(2), 244. doi:10.2307/2065853.
[28] Morwitz, V. G., Steckel, J. H., & Gupta, A. (2007). When do purchase intentions predict sales? International Journal of Forecasting, 23(3), 347–364. doi:10.1016/j.ijforecast.2007.05.015.
[29] Sheeran, P. (2002). Intention—Behavior Relations: A Conceptual and Empirical Review. European Review of Social Psychology, 12(1), 1–36. doi:10.1080/14792772143000003.
[30] Pavlou, P. A., & Fygenson, M. (2006). Understanding and Predicting Electronic Commerce Adoption: An Extension of the Theory of Planned Behavior1. MIS Quarterly, 30(1), 115–143. doi:10.2307/25148720.
[31] Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. doi:10.1016/0749-5978(91)90020-T.
[32] Guo, J., Li, Y., Xu, Y., & Zeng, K. (2021). How Live Streaming Features Impact Consumers’ Purchase Intention in the Context of Cross-Border E-Commerce? A Research Based on SOR Theory. Frontiers in Psychology, 12, 767876. doi:10.3389/fpsyg.2021.767876.
[33] Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176. doi:10.1287/isre.6.2.144.
[34] Quynh, P. N. H., Thu, C. L., Pandey, K. K., & Phuong, N. V. (2025). Impact of Green Marketing Elements on Consumers: A Behavioral Approach. Emerging Science Journal, 9(4), 2244–2260. doi:10.28991/ESJ-2025-09-04-028.
[35] Wen, J., Li, X., & Han, H. (2025). Emotional Resonance and Buying Behavior in Live Streaming: A Study on KOL Influence and the Mediation of Purchase Intentions. Journal of Theoretical and Applied Electronic Commerce Research, 20(2). doi:10.3390/jtaer20020108.
[36] Grewal, D., Monroe, K. B., & Krishnan, R. (1998). The Effects of Price-Comparison Advertising on Buyers’ Perceptions of Acquisition Value, Transaction Value, and Behavioral Intentions. Journal of Marketing, 62(2), 46–59. doi:10.1177/002224299806200204.
[37] Moon, J., Chadee, D., & Tikoo, S. (2008). Culture, product type, and price influences on consumer purchase intention to buy personalized products online. Journal of Business Research, 61(1), 31–39. doi:10.1016/j.jbusres.2006.05.012.
[38] Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69–96. doi:10.1509/jm.15.0420.
[39] Verhoef, P. C., Lemon, K. N., Parasuraman, A., Roggeveen, A., Tsiros, M., & Schlesinger, L. A. (2009). Customer Experience Creation: Determinants, Dynamics and Management Strategies. Journal of Retailing, 85(1), 31-41. doi:10.1016/j.jretai.2008.11.001.
[40] Oliver, R. L. (1999). Whence Consumer Loyalty? Journal of Marketing, 63(4), 33–44. doi:10.1177/00222429990634s105.
[41] Balakrishnan, J., & Griffiths, M. D. (2018). Loyalty towards online games, gaming addiction, and purchase intention towards online mobile in-game features. Computers in Human Behavior, 87, 238-246. doi:10.1016/j.chb.2018.06.002.
[42] Zhang, Y., Albattat, A., Rehman, A. U., & Azam, S. M. F. (2025). Investigating the trust entities that influence consumers’ purchase intention in livestream e-commerce from trust transfer perspective: using analysis of SEM and fsQCA. Cogent Business & Management, 12(1), 2582220. doi:10.1080/23311975.2025.2582220.
[43] Sun, X., Pelet, J. É., Dai, S., & Ma, Y. (2023). The Effects of Trust, Perceived Risk, Innovativeness, and Deal Proneness on Consumers’ Purchasing Behavior in the Livestreaming Social Commerce Context. Sustainability (Switzerland), 15(23), 16320. doi:10.3390/su152316320.
[44] Hilvert-Bruce, Z., Neill, J. T., Sjöblom, M., & Hamari, J. (2018). Social motivations of live-streaming viewer engagement on Twitch. Computers in Human Behavior, 84, 58–67. doi:10.1016/j.chb.2018.02.013.
[45] Gu, M., & Zhao, T. (2025). Research on the purchase intention of museum digital cultural and creative products based on value adoption model. Scientific Reports, 15(1), 2140. doi:10.1038/s41598-025-02140-6.
[46] Tao, M., Alam, F., Lahuerta-Otero, E., & Mengyuan, C. (2024). Get Ready to Buy With Me: The Effect of Social Presence Interaction and Social Commerce Intention on S-commerce Live Streaming. SAGE Open, 14(1), 21582440241232750. doi:10.1177/21582440241232751.
[47] Wu, Y., & Huang, S. (2021). How customer experience affects purchase intention in live-streaming commerce: The mediating roles of trust and perceived value. Information & Management, 58(5), 103486. doi:10.1016/j.im.2021.103486.
[48] Hovland, C. I., & Weiss, W. (1951). The influence of source credibility on communication effectiveness. Public Opinion Quarterly, 15(4), 635–650. doi:10.1086/266350.
[49] Zhang, K. Z. K., Benyoucef, M., & Zhao, S. J. (2015). Consumer participation and gender differences on companies’ microblogs: A brand attachment process perspective. Computers in Human Behavior, 44, 357–368. doi:10.1016/j.chb.2014.11.068.
[50] Chen, Y. C., Shang, R. A., & Kao, C. Y. (2009). The effects of information overload on consumers’ subjective state towards buying decision in the internet shopping environment. Electronic Commerce Research and Applications, 8(1), 48–58. doi:10.1016/j.elerap.2008.09.001.
[51] Eppler, M. J., & Mengis, J. (2004). The concept of information overload: A review of literature from organization science, accounting, marketing, MIS, and related disciplines. Information Society, 20(5), 325–344. doi:10.1080/01972240490507974.
[52] Cao, X., Masood, A., Luqman, A., & Ali, A. (2018). Excessive use of mobile social networking sites and poor academic performance: Antecedents and consequences from stressor-strain-outcome perspective. Computers in Human Behavior, 85, 163–174. doi:10.1016/j.chb.2018.03.023.
[53] Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544–564. doi:10.1016/j.dss.2007.07.001.
[54] Ali, F., Amin, M., & Cobanoglu, C. (2016). An Integrated Model of Service Experience, Emotions, Satisfaction, and Price Acceptance: An Empirical Analysis in the Chinese Hospitality Industry. Journal of Hospitality Marketing & Management, 25(4), 449–475. doi:10.1080/19368623.2015.1019172.
[55] Ranjith, P., Nisansala, S., Jayasingha, N., Weerasekara, K., Wisenthige, K., & Dayapathirana, N. (2025). Does social media information credibility influence social commerce purchase intention of skincare products? Evidence from Facebook. Plos One, 20(10 October), 334126. doi:10.1371/journal.pone.0334126.
[56] Yan, D., Marzuk, A. Bin, Yang, J., Zhou, J., & Tao, S. (2025). Bibliometric Analysis of Smart Tourism Destination: Knowledge Structure and Research Evolution (2013–2025). Tourism and Hospitality, 6(4), 194. doi:10.3390/tourhosp6040194.
[57] Shui, X., Bian, S., & Zhang, P. (2025). How Can AI Virtual Streamers Gain Consumer Trust to Influence Purchase Intention in Live-Streaming E-Commerce? Journal of Theoretical and Applied Electronic Commerce Research, 20(4), 325. doi:10.3390/jtaer20040325.
[58] Wang, X., Yu, C., & Wei, Y. (2012). Social Media Peer Communication and Impacts on Purchase Intentions: A Consumer Socialization Framework. Journal of Interactive Marketing, 26(4), 198–208. doi:10.1016/j.intmar.2011.11.004.
[59] Hu, C., Niu, P., Chen, X., Cheng, P., Jiang, X., Li, R., & Kuang, R. (2026). Does cultural identity catalyze behavior? A TAM-based study on museum cultural creative products consumption in China. PloS One, 21(2), e0341346. doi:10.1371/journal.pone.0341346.
[60] Wu, Z., Zhang, H., & Wang, X. (2025). Correlation between Agricultural Product Purchases and Live-Streaming Economy in the Digital Economy. HighTech and Innovation Journal, 6(4), 1350–1360. doi:10.28991/HIJ-2025-06-04-013.
[61] Xia, L., Monroe, K. B., & Cox, J. L. (2004). The price is unfair! A conceptual framework of price fairness perceptions. Journal of Marketing, 68(4), 1–15. doi:10.1509/jmkg.68.4.1.42733.
[62] Zheng, X., Zhu, S., & Lin, Z. (2013). Capturing the essence of word-of-mouth for social commerce: Assessing the quality of online e-commerce reviews by a semi-supervised approach. Decision Support Systems, 56, 211–222. doi:10.1016/j.dss.2013.06.002.
[63] Huang, Z., Zhu, Y., Hao, A., & Deng, J. (2023). How social presence influences consumer purchase intention in live video commerce: the mediating role of immersive experience and the moderating role of positive emotions. Journal of Research in Interactive Marketing, 17(4), 493–509. doi:10.1108/JRIM-01-2022-0009.
[64] Chen, Y. H., Lin, I. K., Huang, C. I., & Chen, H. S. (2024). How Key Opinion Leaders’ Expertise and Renown Shape Consumer Behavior in Social Commerce: An Analysis Using a Comprehensive Model. Journal of Theoretical and Applied Electronic Commerce Research , 19(4), 3370–3385. doi:10.3390/jtaer19040163.
[65] Anderson, J. C., & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 411–423. doi:10.1037/0033-2909.103.3.411.
[66] Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. doi:10.1080/10705519909540118.
[67] Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. doi:10.1177/002224378101800104.
[68] Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. doi:10.2753/MTP1069-6679190202.
[69] Kline, R.B. (2011) Principles and Practice of Structural Equation Modeling. The Guilford Press, New York, United States.
[70] MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149. doi:10.1037/1082-989X.1.2.130.
[71] Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60. doi:10.21427/D7CF7R.
- This work (including HTML and PDF Files) is licensed under a Creative Commons Attribution 4.0 International License.
