Information Transparency and Consumer Education: Governance Strategies to Counter "Big Data Price Discrimination"

Chen Jinghao, Deng Zhiyuan, Chen Yide

Knowledge Management Forum ›› 2025, Vol. 10 ›› Issue (6) : 516-534.

PDF(3409 KB)
PDF(3409 KB)
Knowledge Management Forum ›› 2025, Vol. 10 ›› Issue (6) : 516-534. DOI: 10.13266/j.issn.2095-5472.2025.035  CSTR: 32306.14.CN11-6036.2025.035

Information Transparency and Consumer Education: Governance Strategies to Counter "Big Data Price Discrimination"

Author information +
History +

Abstract

[Purpose/Significance] Addressing the issue of "big data price discrimination" in the digital economy, which severely undermines consumer rights and market fairness, this study focuses on two key governance strategies: information transparency and consumer education. It explores their synergistic efficacy in countering this phenomenon to foster a fair digital market with multi-stakeholder participation. [Method/Process] Based on information asymmetry theory, equity theory, and information processing theory, the research employs two 2×2 scenario-based experiments (food package ordering and hotel booking) to examine the interactive effect of information transparency and consumer education on perceived price discrimination, and analyzes the mediating effect of perceived price fairness. [Result/Conclusion] The results indicate that the interaction between information transparency and consumer education significantly enhances consumers' perception of price discrimination. While enhancing either strategy individually improves recognition ability, their combined effect yields more pronounced results. Perceived price fairness partially mediates this interactive influence: improvements in information transparency and consumer education enhance consumers' understanding of pricing procedures, thereby increasing their perception of fairness and indirectly mitigating their ultimately negative judgments.

Key words

information transparency / consumer education / big data price discrimination

Cite this article

Download Citations
Chen Jinghao , Deng Zhiyuan , Chen Yide. Information Transparency and Consumer Education: Governance Strategies to Counter "Big Data Price Discrimination"[J]. Knowledge Management Forum. 2025, 10(6): 516-534 https://doi.org/10.13266/j.issn.2095-5472.2025.035

References

[1]
李飞翔. “大数据杀熟”背后的伦理审思、治理与启示[J]. 东北大学学报(社会科学版), 2020, 22(1): 7-15.
LI F X. Ethical reflections, governance and implications under the background of big data price discrimination[J]. Journal of Northeastern University (social science edition), 2020, 22(1): 7-15.
[2]
梁正, 曾雄. “大数据杀熟”的政策应对: 行为定性、监管困境与治理出路[J]. 科技与法律(中英文), 2021(2): 8-14.
LIANG Z, ZENG X. Policies for "using big-data analysis to swindle existing customers": its legal attribute, regulation difficulties and governance approaches[J]. Science technology and law, 2021, (2): 8-14.
[3]
汪庆华. 算法透明的多重维度和算法问责[J]. 比较法研究, 2020(6): 163-173.
WANG Q H. The multiple dimensions of algorithmic transparency and algorithmic accountability[J]. Journal of comparative law, 2020(6): 163-173.
[4]
ZARSKY T. The trouble with algorithmic decisions: an analytic road map to examine efficiency and fairness in automated and opaque decision making[J]. Science, technology & human values, 2016, 41(1): 118-132.
[5]
许明月, 陈小维. “大数据杀熟”行为的法律规制——以消费者权益保护为视角[J]. 西南石油大学学报(社会科学版), 2021, 23(6): 72-80.
XU M Y, CHEN X W. Legal regulation of "big data discriminatory pricing": a discussion from the perspective of consumer protection[J]. Journal of Southwest Petroleum University (social science edition), 2021, 23(6): 72-80.
[6]
王秋梅. “大数据杀熟”的演变轨迹、治理困境与协同共治[J]. 南京邮电大学学报(社会科学版), 2025, 27(3):72-79, 108.
WANG Q M. The evolution trajectory, governance dilemma and collaborative governance of "big data price discrimination"[J]. Journal of Nanjing University of Posts and Telecommunications (social science edition), 2025, 27(3):72-79, 108.
[7]
AKERLOF G. The market for "lemons": quality uncertainty and the market mechanism[M]//ESTRIN S, MARIN A. Essential readings in economics. London: Macmillan Education, 1995: 175-188.
[8]
承上. 人工智能时代个性化定价行为的反垄断规制——从大数据杀熟展开[J]. 中国流通经济, 2020, 34(5): 121-8.
CHENG S. Antitrust enforcement against personalized pricing in the artificial intelligence era: starting from the big data-enabled price discrimination[J]. China circulation economy, 2020, 34(5): 121-128.
[9]
胡元聪, 冯一帆. 大数据杀熟中消费者公平交易权保护探究[J]. 陕西师范大学学报(哲学社会科学版), 2022, 51(1): 161-76.
HU Y C, FENG Y F. An explanation as to the protection of the consumer’s fair trading right in differential pricing by big data technology[J]. Journal of Shaanxi Normal University (philosophy and social sciences edition), 2022, 51(1): 161-176.
[10]
姚佳. 个人信息主体的权利体系——基于数字时代个体权利的多维观察[J]. 华东政法大学学报, 2022, 25(2): 87-99.
YAO J. The right system of personal information subject: a multi-dimensional observation of individual rights in the digital age[J]. Journal of East China University of Political Science and Law, 2022, 25(2): 87-99.
[11]
吴志艳, 罗继锋. 算法价格歧视和顾客感知背叛[J]. 上海对外经贸大学学报, 2022, 29(5): 108-124.
WU Z Y, LUO J F. Algorithmic price discrimination and customer perceived betrayal[J]. Journal of Shanghai University of International Business and Economics, 2022, 29(5): 108-124.
[12]
张惠舒, 赵宇翔, 宋士杰. 信息弱势群体算法素养的形成机理与影响因素——以短视频平台为例[J]. 图书情报知识, 2024, 41(2): 127-137.
ZHANG H S, ZHAO Y X, SONG S J. The formation mechanism and influencing factors of algorithmic literacy of information vulnerable groups: evidence from short video platforms[J]. Documentation, information & knowledge, 2024, 41(2): 127-137.
[13]
郑鹏程, 龙森. 公共性视角下平台“大数据杀熟”的规制逻辑与路径[J]. 吉首大学学报(社会科学版), 2022, 43(6): 29-40.
ZHENG P C, LONG S. The regulatory logic and path of "big data price discrimination" by platforms from the perspective of publicity[J]. Journal of Jishou University (social sciences edition), 2022, 43(6): 29-40.
[14]
郑海英. 数字经济时代电商平台定价策略选择研究——基于价格透明度的分析[J]. 价格理论与实践, 2019(11): 121-124.
ZHENG H Y. Research on pricing strategy selection of e-commerce platform in the era of digital economy: analysis based on price transparency[J]. Price: theory & practice, 2019(11): 121-124.
[15]
FERGUSON J, ELLEN P. Transparency in pricing and its effect on perceived price fairness[J]. Journal of product and brand management, 2013, 22(5/6): 404-412.
[16]
苏岚岚, 彭艳玲. 数字化教育、数字素养与农民数字生活[J]. 华南农业大学学报(社会科学版), 2021, 20(3): 27-40.
SU L L, PENG Y L. Digital education, digital literacy and farmers' participation in digital life[J]. Journal of South China Agricultural University (social science edition), 2021, 20(3): 27-40.
[17]
NGUYEN T Q, NGOC P T A, PHUONG H A, et al. Digital competence of Vietnamese citizens: an application of digcomp framework and the role of individual factors[J]. Education and information technologies, 2024, 29(15): 19267-19298.
[18]
TINMAZ H, LEE Y-T, FANEA-IVANOVICI M, et al. A systematic review on digital literacy[J]. Smart learning environments, 2022, 9(1): 21.
[19]
BETTMAN J. An information processing theory of choice[M]. Reading: Addison-Wesley, 1979.
[20]
ADAMS J. Toward an understanding of inequity[J]. The journal of abnormal and social psychology, 1963, 67(5): 422-436.
[21]
XIA L, MONROE K, COX J, et al. The price is unfair! a conceptual framework of price fairness perceptions[J]. Journal of marketing, 2004, 68(4): 1-15.
[22]
MARTIN W C, PONDER N, LUEG J E. Price fairness perceptions and customer loyalty in a retail context[J]. Journal of business research, 2009, 62(6): 588-593.
[23]
邓湘雪. 顾客教育对顾客感知质量和顾客承诺关系的调节作用——以理财产品为例[D]. 长春: 东北师范大学, 2015.
DENG X X. The regulatory effect of customer education on the relationship between perceived service quality and customer commitment: a case study of financial products[D]. Changchun: Northeast Normal University, 2015.
[24]
LIU Y. The role of transparency in consumer brand relationships[J]. Imperial college London, 2013.
[25]
游志强. 大数据杀熟对消费者持续使用意愿的影响研究[D]. 泉州: 华侨大学, 2021.
YOU Z Q. The empirical study of the impact of big data-based price discrimination on consumer's continuance intention[D]. Quanzhou: Huaqiao University, 2021.
[26]
ZHAO X, LYNCH J, CHEN Q. Reconsidering Baron and Kenny: myths and truths about mediation analysis[J]. Journal of consumer research, 2010, 37(2): 197-206.
[27]
HAWS K, BEARDEN W. Dynamic pricing and consumer fairness perceptions[J]. Journal of consumer research, 2006, 33(3): 304-311.
[28]
BOLTON L E, WARLOP L, ALBA J W. Consumer perceptions of price (un)fairness[J]. Journal of consumer research, 2003, 29(4): 474-491.
[29]
邓胜利, 许家辉, 夏苏迪. 数字环境下大学生算法素养评价体系及实证研究[J]. 图书情报工作, 2023, 67(2): 23-32.
DENG S L, XU J H, XIA S D. Evaluation system and empirical research on algorithm literacy of college students in digital environment[J]. Library and information service, 2023, 67(2): 23-32.
[30]
夏苏迪, 邓胜利, 付少雄, 等. 数智时代的算法素养: 内涵、范畴及未来展望[J]. 图书情报知识, 2023, 40(1): 23-34.
XIA S D, DENG S L, FU S X, et al. Algorithm literacy in digital and intelligence era: connotation, category and prospect[J]. Documentation, information & knowledge, 2023, 40(1): 23-34.
[31]
张明鑫, 朱侯. 隐私政策“霸王条款”特征及其作用机制的内容分析[J]. 情报学报, 2023, 42(9): 1092-1102.
ZHANG M X, ZHU H. Characteristics of "malicious terms" in privacy policies and their interactive mechanisms based on content analysis[J]. Journal of the China Society for Scientific and Technical Information, 2023, 42(9): 1092-1102.
[32]
HOFSTEDE G. Culture's consequences: international differences in work-related values[M]. Beverly Hills, CA: SAGE Publications, 1984.

陈璟浩:提出研究构思,进行正式分析,获取经费资助,设计研究方法,指导研究过程;

邓至媛:管理实验数据,进行正式分析,开展调查工作,完成数据可视化,撰写论文初稿;

陈一德:进行正式分析,验证实验结果,开展调查工作,修改论文并定稿。

PDF(3409 KB)

Accesses

Citation

Detail

Sections
Recommended

/