An Assessment of Multi-dimensional Factors Influencing Patronage of E-Commerce Channels in Beijing, China: Inputs for Loyalty Program

Fang  Liu,

An Assessment of Multi-dimensional Factors Influencing Patronage of E-Commerce Channels in Beijing, China: Inputs for Loyalty Program

Discipline: business and management (non-specific)

Abstract:

Cognizant of the growing Chinese e-commerce as one of the fundamental elements of the modern world because of technological advancements, this empirical study investigated e-businesses that utilize a variety of digital channels, such as social media, websites, and specialized applications, to market their products. Through a quantitativedescriptive research method, this study assessed the factors influencing e-commerce patronage, including product type, product quality, pricing competitiveness, user experience, and information security. The respondents were 300 customers of Tiktok, TaoBao, and JingDong in Beijing, China, chosen through quota sampling, who completed a survey questionnaire as the primary instrument for gathering data to answer research problems and test the hypothesis. The results revealed that user experience is highly influential in e-commerce patronage. The impact of these elements on patronage may vary depending on user preferences, platform design, and the overall shopping journey. The availability of a wide range of products on e-commerce platforms attracts customers looking for diverse options, influencing their patronage decisions. Competitive pricing strategies, including discounts, promotions, and price comparisons, significantly influence customers’ choice of e-commerce channels. Trustworthiness and security of payment methods, data protection, and overall transaction security play a crucial role in attracting and retaining customers. The factors influencing e-commerce patronage are not significantly affected by demographic characteristics such as age, sex, educational attainment, and income.

References:

Best, J. W., & Kahn, J. V. (2006). Research in Education (10th Editi). Cape Town: Pearson Education Inc.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS quarterly, 351-370.
Dai, W., Arnulf, J. K., Iao, L., Wan, P., & Dai, H. (2019). Like or want? Gender differences in attitudes toward online shopping in China. Psychology & Marketing, 36(4), 354-362.
Davis, F. D. (1989). Technology acceptance model: TAM. Al-Suqri, MN, Al-Aufi, AS: Information Seeking Behavior and Technology Adoption, 205, 219.
Etikan, I., & Bala, K. (2017). Sampling and sampling methods. Biometrics & Biostatistics International Journal, 5(6), 00149.
Hao, K., & Kim, H. D. (2020). A Study on the Activation of Cross Border E-commerce in China. e-비즈니스연구, 21(1), 189-202.
He, Y., & Wang, J. (2019). A panel analysis on the cross border e-commerce trade: Evidence from ASEAN countries. The Journal of Asian Finance, Economics and Business, 6(2), 95-104.
Jayasankara Prasad, C., & Ramachandra Aryasri, A. (2011). Effect of shopper attributes on retail format choice behaviour for food and grocery retailing in India. International Journal of Retail & Distribution Management, 39(1), 68-86.
Kanaveedu, A., & Kalapurackal, J. J. (2022). Influencer marketing and consumer behaviour: A systematic literature review. Vision, 09722629221114607.
Lee, C., & Lee, E. (Eds.). (2019). E-commerce, competition & ASEAN economic integration. ISEAS-Yusof Ishak Institute.
Li, L., Yuan, L., & Tian, J. (2023). Influence of online E-commerce interaction on consumer satisfaction based on big data algorithm. Heliyon, 9(8).
Lu, C. W., Lin, G. H., Wu, T. J., Hu, I. H., & Chang, Y. C. (2021). [Retracted] Influencing Factors of Cross‐Border E‐Commerce Consumer Purchase Intention Based on Wireless Network and Machine Learning. Security and Communication Networks, 2021(1), 9984213.
Makhitha, K. (2023). Attributes Influencing Consumers’ Selection of a Shopping Centre: The Demographic Impact. Expert Journal of Marketing, 11(1).
McCombes, S. (2019). Descriptive research design| definition, methods and examples. Retrieved from Scribbr website: https://www.scribbr.com/methodology/descriptive-research.
Mofokeng, T. E. (2021). The impact of online shopping attributes on customer satisfaction and loyalty: Moderating effects of e-commerce experience. Cogent Business & Management, 8(1), 1968206.
Mou, J., Cui, Y., & Kurcz, K. (2019). Bibliometric and visualized analysis of research on major e-commerce journals using Citespace. Journal of electronic commerce research, 20(4), 219-237.
Wang, T. (2023). Research on the Impact of E-commerce on Offline Retail Industry. Frontiers in Business, Economics and Management, 10(1), 169-173.
Yan, T. (2022). The Impact of Live Streaming E-Commerce Features on Chinese Consumers’ Attitude and Purchase Intention (Master's thesis, Syracuse University).