Analysis and Practice of the Synergistic Application of Four Methods and Two Software in Tourism Market Research

DOI: https://doi.org/10.62517/jse.202511604

Author(s)

Zhengxin Chang

Affiliation(s)

Tourism Management Major, Business, School, Tianjin University of Finance and Economics, Tianjin, China

Abstract

Moderating effect, mediating effect, one-way analysis of variance (ANOVA), and two-way/multi-way ANOVA are important analytical methods in the field of tourism market and tourism research. Among them, the moderating effect can reveal the differences in variable relationships under different conditions; the mediating effect can analyze the internal mechanism of action between variables; one-way ANOVA can effectively compare the significant differences in tourism preferences and behaviors among different groups (e.g., age, region); and two-way/multi-way ANOVA further explores the comprehensive impact of the interaction of multiple factors on tourism phenomena. This paper systematically integrates textbooks, online courses, and academic literature, and uses SPSS and R language software to deeply explain the theory, calculation process, and practical application of the above four methods, laying a foundation for subsequent tourism research. Due to the large theoretical system of the four methods and the limitations of the author's research time, energy, and funds, this paper has not yet deeply explored the linear regression foundation required for moderating effect and mediating effect, the application of R language mediating effect visualization tools (e.g., mediationPlot package), and the processing strategy when data is not significant in two-way/multi-way ANOVA, which will be further studied in the future.

Keywords

Tourism Market Research; Market Analysis; Mediating Effect; Moderating Effect; Analysis of Variance (ANOVA)

References

[1] Robinson C , Schumacker R E .Interaction Effects: Centering, Variance Inflation Factor, and Interpretation Issues[J]. 2009. [2] Chen D , Zhang W , Bi J ,et al.Hosts' online affinities and their impacts on the number of online reviews on peer-to-peer platforms[J].Tourism Management [2025-06-12]. [3] Chen Dongzhi, Qiu Hanqin. A Study on the Influence of Hosts' Self-reported Content on Homestay Sales -- From the Perspective of Social Cognitive Theory[J]. Tourism Science, 2024, 38(10): 100-127. [4] Wang Caicai, Qiu Yisi, Xu Hong, et al. The Impact of Digital Transformation of Rural Homestays on Survival Resilience -- The Mediating Effect of "Dual-stage Dynamic Capability"[J]. Tourism Tribune, 2025(5). [5] Lv X , Zhang K , Song Q ,et al.How does occupational stigma and work dirtiness inhibit hotel front-line employees' proactive customer service performance and its solutions[J].Tourism Management, 2024, 104(000). [6] Qiu, H., Chen,D.*, Lyu, J., He, H. Li, C.(2021). Affinity-seeking strategies of homestay hosts: Scale development and validation, Journal of Hospitality and Tourism Management, 49(2021), 195-203. [7] Yan, R., Tang, Z., & Liu, D. (2024). Can virtual streamers replace human streamers? The interactive effect of streamer type and product type on purchase intention. Marketing Intelligence & Planning, 43(2). [8] Zhen, X., Wang, P., & Li, X. (2024). The Streamer’s sales strategy choice considering sales effort. Journal of Retailing and Consumer Services, 78, 103745. [9] Zhang K, Luo B, Yan J, et al. The art and impact of narrative: How streamer narrative styles shape consumers’ purchase intention[J]. Journal of Retailing and Consumer Services, 2025, 87: 104357. [10] Liu H, Zhang P, Cheng H, et al. Impact of AI-generated virtual streamer interaction on consumer purchase intention: A focus on social presence and perceived value[J]. Journal of Retailing and Consumer Services, 2025, 85: 104290.