社会化商务中基于经验及推荐的消费者感知信任模糊融合模型

doi:10.16381/j.cnki.issn1003-207x.2020.01.010

Abstract

Abstract: With the booming of social commerce in recent years, trust fusion in social networks has become a crucial factor in consumer's decision making. Consumers establish perceived trust based on personal experience and recommendation, whose essence is multi-sources trust fusion. Trust fusion model originating from computer science has been fully analyzed by scholars worldwide. In social commerce, similarities between new decision making and experiential decision making, as well as recommendations play an important role in consumers' decision making. However, some new challenges have emerged in social commerce due to the fuzziness and multi-sources of consumers' perceived trust. Therefore, multi-sources trust fusion of consumers' trust in social commerce needs to be further analyzed.
Focusing on the fuzziness of consumers' perceived trust, a fuzzy trust fusion model is established by combining cased-based decision theory (CBDT) and multi-attribute decision making based on intuitionistic fuzzy sets. Consumers' perceived trust stemmed from experience and recommendation, hence our model is composed of three parts in working process:empirical trust calculation, recommendation trust calculation and trust fusion of both these two. The key influencing factors of perceived trust have been integrated into multi-attribute decision making based on intuitionistic fuzzy sets, whereas empirical trust and recommendation trust have been calculated respectively within the framework of CBDT, both fused grounded on anchoring effect.
The effectiveness of our model has been tested by case study and data analysis. The impact of personal experience, similarity and consensus operator on perceived trust has been illustrated to reveal the process of transformation from experience and recommendation to perceived trust. In the data analysis, the data has been collected by questionnaire, and the calculation result of perceived trust has been compared with the survey data. The viability and effectiveness of our results on perceived trust were validated in comparison and improved by prediction accuracy.
Combining decision maker's experience and recommendation, our model merge several methods such as CBDT and intuitionistic fuzzy sets which enable us to refine the trust fusion model research with the frame and new perspectives. With the assistance of the proposed method for perceived trust measurement, a new way for E-commerce platform is provided to make precise marketing strategy through consumers' online reviews and related social relationship.

Key words: social commerce, trust fusion, perceived trust, intuitionist fuzzy set, case-based decision theory

CLC Number:

F713

YIN Jin, HU Xiang-pei, ZHENG Yi, ZHOU Zi-xuan. Fuzzy Fusion Model of Consumers’ Perceived Trust Based on Experience and Recommendation in Social Commerce[J]. Chinese Journal of Management Science, 2020, 28(1): 122-133.

References

[1] 卢云帆,鲁耀斌,林家宝,等. 社会化商务中顾客在线沟通研究:影响因素和作用规律[J]. 管理评论, 2014,26(4):111-121.
[2] Stephen A T, Toubia O. Deriving value from social commerce networks[J]. Journal of Marketing Research, 2010, 47(2): 215-228.
[3] 王怡, 梁循, 付虹蛟,等. 社会网络中信息的扩散机理及其定量建模[J]. 中国管理科学, 2017,25(12):147-157.
[4] 张洪. 社会化商务环境下顾客交互行为研究[D]. 武汉:华中科技大学, 2014.
[5] Audun J. The consensus operator for combining beliefs[J]. Artificial Intelligence, 2002,141(1): 157-170.
[6] 宋国, 峰梁. 一种基于用户行为信任的云安全访问控制模型[J]. 中国管理科学,2013,(S2):669-676.
[7] Blaze M, Feigenbaum J, Lacy J. Decentralized trust management[C]// Proceedings of 1996 IEEE Symposium on Security and Privacy, Oakland, USA,May6-8, 1996.
[8] Jøsang A. An Algebra for Assessing Trust in Certification Chains[C]//Proceedings of the Network and Distributed Systems Security Symposium, San Diego, USA, February 3-5, 1999.
[9] 田博,覃正. B2C电子商务中基于D-S证据融合理论的推荐信任评价模型[J].管理科学,2008,21(5): 98-104.
[10] Liu Guanfeng, Wang Yan, Orgun M A. Strong Social component-aware trust sub-network extraction in contextual social networks[C]//Proceedings of IEEE International Conference on Web Services, San Francisco, Canada, June 27-July2, 2016.
[11] 尤天慧, 张瑾, 樊治平. 基于在线评价信息和消费者期望的商品选择方法[J]. 中国管理科学, 2017,25(11):94-102.
[12] Ziegler C N, Golbeck J. Investigating interactions of trust and interest similarity[J]. Decision Support Systems, 2006, 43(2):460-475.
[13] Li Yungming, Wu Chunte, Lai Chengyang. A social recommender mechanism for e-commerce: Combining similarity, trust, and relationship[J]. Decision Support Systems, 2013, 55(3):740-752.
[14] Verberne F M, Ham J, Midden C J. Trusting a virtual driver that looks, acts, and thinks like you[J]. Human Factors: The Journal of the Human Factors and Ergonomics Society, 2015, 57(5):895-909.
[15] Al Falasi H, Masud M M, Mohamed N. Trusting the same: Using similarity to establish trust among vehicles[C]// Proceedings of International Conference on Collaboration Technologies and Systems, Atlanta, USA June 1-5, 2015.
[16] Lount Jr R B. The impact of positive mood on trust in interpersonal and intergroup interactions[J]. Journal of Personality & Social Psychology, 2010, 98(3):420-433.
[17] Aha D W, Breslow L A, Muñoz-Avila H. Conversational case-based reasoning[J]. Applied Intelligence, 2001, 14(1):9-32.
[18] Smyth B, Champin P A. The experience web: A case-based reasoning perspective[C]// Proceedings of International Joint Conference on Artificial Intelligence, California, USA, July 11-17, 2009.
[19] Roldan R E, Negny S, Cortes R G. Improvement of online adaptation knowledge acquisition and reuse in case-based reasoning[J]. Engineering Applications of Artificial Intelligence, 2015, 41(C):1-16.
[20] Schank R C. Dynamic memory: A theory of reminding and learning in computers and people[M]. New York: Cambridge University Press, 1982.
[21] Gilboa I, Schmeidler D. Case-based decision theory[J]. Quarterly Journal of Economics, 1992, 110(3):605-639.
[22] Grosskopf B, Sarin R, Watson E. An experiment on case-based decision making[J]. Theory and Decision, 2015, 79(4):639-666.
[23] 王翯华, 朱建军, 方志耕. 基于案例分析的语言信息灰靶决策分类模型[J]. 系统工程理论与实践, 2013, 33(12):3172-3181.
[24] 李永海, 樊治平, 袁媛. 基于相似历史案例分析的突发事件应急方案生成方法[J]. 系统工程, 2014,32(4):76-81.
[25] 李永海, 陈曦, 张尧,等. 基于CBDT的新产品开发项目风险应对方案选择方法[J]. 管理工程学报, 2015, 29(3):257-264.
[26] 乐琦. 直觉模糊环境下考虑匹配意愿的双边匹配决策[J]. 中国管理科学, 2017, 25(6): 161-168.
[27] 李登峰.直觉模糊集决策与对策分析方法[M].北京:国防工业出版社,2012.
[28] Golbeck J. Trust and nuanced profile similarity in online social networks[J]. Acm Transactions on the Web, 2009, 3(4):1-33.
[29] Ziegler C N, Lausen G. Analyzing correlation between trust and user similarity in online communities[J]. 2004, 2995:251-265.
[30] Guo G, Zhang J, Yorke-Smith N. Leveraging multiviews of trust and similarity to enhance clustering based recommender systems[J]. Knowledge-Based Systems, 2015, 74(1):14-27.
[31] 刘志明,刘鲁. 微博网络舆情中的意见领袖识别及分析[J].系统工程,2011,29(6):8-16.
[32] Summers J O. The identity of women's clothing fashion opinion leaders[J]. Journal of Marketing Research, 1970,7(2):178-185.
[33] Bansal H S, Voyer P A. Word-of-mouth processes within a services purchase decision context[J]. Journal of Service Research, 2003,3(2):166-177.
[34] Friedman H H, Friedman L. Endorser effecttiveness by product type[J]. Journal of Advertising Research, 1979,19(5): 63-71.
[35] 梦非. 社会化商务环境下意见领袖对购买意愿的影响研究[D].南京:南京大学,2012.
[36] Shin D H. User experience in social commerce: In friends we trust[J]. Behaviour & Information Technology, 2013, 32(11):1191-1192.
[37] Berger J. Word of mouth and interpersonal communication: A review and directions for future research[J]. Journal of Consumer Psychology, 2014, 24(4): 586-607.
[38] Saadi R, Hasan O, Pierson J M. Establishing trust beliefs based on a uniform disposition to trust[C]// International IEEE Conference on Signal-image Technologies & Internet-based System. IEEE, 2007:68-95.
[39] Yan S, Zheng X L, Wang Y. A graph-based comprehensive reputation model: exploiting the social context of opinions to enhance trust in social commerce[J]. Information Sciences, 2015, 318(10): 51-72.
[40] Granovetter M, Soong R. Threshold models of interpersonal effects in consumer demand[J]. Journal of economic behavior & organization, 1986, 7(1): 83-99.
[41] Bente G, Baptist O, Leuschner H. To buy or not to buy: Influence of seller photos and reputation on buyer trust and purchase behavior[J]. 2012, 70(1):1-13.
[42] Wang Shangguang, Huang Lin, Hsu Chinghsien, et al. Collaboration reputation for trust-worthy Web service selection in social networks[J]. Journal of Computer & System Sciences, 2016, 82(1):130-143.
[43] Bharadwaj K K, Mohammad Y H, Al-Shamri. Fuzzy computational models for trust and reputation systems[J]. Electronic Commerce Research & Applications, 2009, 8(1):37-47.
[44] Nu D, Ez-Gonzalez J, Manuel A,et al. Reputation features for trust prediction in social networks[J]. Neurocomputing, 2015, 166(C):1-7.
[45] Tversky A, Kahneman D. Judgment under uncertainty: Heuristics and biases[J]. Uncertainty in Economics, 1973, 185(4157):1124-1131.
[46] 韩金星, 张喆, 古晨妍. 网络团购中消费者社会互动对团购信任的影响[J]. 管理评论,2016,28(9):148-162.
[47] Keysar B, Barr D J, Balin J A,et al. Taking perspective in conversation: The role of mutual knowledge in comprehension[J]. Psychological Science, 2000, 11(1):32.
[48] Epley N, Keysar B, Van Boven L, et al. Perspective taking as egocentric anchoring and adjustment[J]. Social Science Electronic Publishing, 2004, 87(3):327-339.

Fuzzy Fusion Model of Consumers’ Perceived Trust Based on Experience and Recommendation in Social Commerce

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 2

Metrics

Comments

Recommended 10

[1]	SHAO Peng, HU Ping. Untruthful Opinions Idenfication and Product Adoption in Consumer Advice Network [J]. Chinese Journal of Management Science, 2019, 27(8): 96-106.
[2]	HAN Jing, YE Shun-xin, CHAI Jian, LI Jian-qiang. Case-Based Decision Analysis Method based on Regret Theory for Hybrid Multiple Attributes Decision Making [J]. Chinese Journal of Management Science, 2016, 24(12): 108-116.