Abstract
Trust is an important term in the context of E-Commerce. It lies at the top in the present trend of E-Commerce. Trust lists the diverse prospects of trustworthiness that exist between the merchant and customer, inducing a better customer liking and Business-to-Customer (B2C) E-Commerce. Considering the imprecise nature of E-Commerce trust, various researchers proposed different trust models and integrated them with fuzzy logic to handle inherent uncertainty. Conventional models of trust are based on subjective logic which falls short in mapping the real-time environment of E-commerce that deals with tentative behavioural values. Though fuzzy logic representation of the facts is a way to deal with improbability but it fails to capture the indeterminacy and false values given by respondents during survey. Authors in this chapter have attempted to target the indeterminacy involved while capturing the perception of respondents during survey for any website. Quite recently, neutrosophic logic (NL) has been proposed by Florentine Smarandache that gives a mathematical model for representing uncertainty, vagueness, ambiguity, imprecision, incompleteness, inconsistency, redundancy and contradictions. All the factors stated are very integral to human thinking, as it is very rare that we tend to conclude/judge in definite environments, imprecision of human systems could be due to the imperfection of knowledge that the human receives (observation) from the external world. Imperfection leads to a doubt about the value of a variable, a decision to be taken or a conclusion to be drawn for the actual system. This chapter suggests computation of perceived trust value by integrating a neutrosophic logic with the proposed fuzzy based trust model that considers all the chief features which affect the trust in E-Commerce.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ba S, Whinston AB, Zhang H (1999) Building trust in the electronic market through an economic incentive mechanism. In: Proceedings of the 20th international conference on information systems, Charlotte, North Carolina, Omnipress, pp 208–213
Ba S, Pavlou PA (2002) Evidence of the effect of trust building technology in electronic markets: price premiums and buyer behavior. MIS Q 26:243–268
Hoffman DL, Novak TP, Peralta M (1999) Building consumer trust online. Commun of the ACM 42:4
Benoit J, John I (2006) Consumer TRUST in E-commerce. Copyright © 2006, Idea Group Inc
Andrea O, Jana D (2006) Trust in E-technologies. Copyright © 2006, Idea Group Inc., distributing in print or electronic forms without written permission of IGI is prohibited
Jarvenpaa SL, Tractinsky N, Vitale, M (1999) Consumer trust in an internet store. Inf Technol Manage 1(1/2):45–72. 5 Gefen D (2000) E-Commerce: the role of familiarity and trust. Omega 28(6):724–737
Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353. ISSN 0019-9958
Clyde WH, Sharath S (2005) The dynamics of trust in B2C e-commerce: a research model and agenda. IseB 3(4):377–403
Kim DJ, Song YI, Braynov SB, Rao HR (2005) Multidimensional trust formation model in B-to-C e-commerce: a conceptual framework and content analyses of academia/ practitioner perspectives. Decis Support Syst 40(2):143–165
Krauter SG, Kaluscha EA (2003) Empirical research in online trust: a review and critical assessment. Int J Hum Comput Stud 58(6):783–812
McKnight DH, Choudhury V, Kacmar C (2002) The impact of initial consumer trust on intentions to transact with a web site: a trust building model. J Strateg Inf Syst 11(3):297–323
Zhuang H, Wongsoontorn S, Zhao Y (2003) A fuzzy-logic based trust model and its optimization for e-commerce. In: F Florida conference on the recent advances in robotics (FCRAR 2003)
Akhter F, Hobbs D, Maamar Z (2005) A fuzzy logic-based system for assessing the level of business-to-consumer (B2C) trust in electronic commerce. Expert Syst Appl 28(4):623–628. ISSN 0957-4174
Nilashi M, Fathian M, Gholamian MR, bin Ibrahim O (2010) Offering a model of evaluation of trust suggesting between customers and E-stores (B2C) based on approaches of fuzzy logic. Int J Bus Res Manage (IJBRM) 1(2):46
Qin Z, Tian B (2007) A trust evaluation model for B2C E-commerce. In: IEEE International Conference on IEEE Service Operations and Logistics, and Informatics, 2007, SOLI 2007
Nefti S, Meziane F, Kasiran K (2005) A fuzzy trust model for E-Commerce. In: Proceedings of the Seventh IEEE International Conference on E-Commerce Technology (CEC ’05). IEEE Computer Society, Washington, DC, USA, pp 401–404. doi:10.1109/ICECT.2005
Kim D, Benbasat I (2003) Trust-related arguments in internet stores: a framework for evaluation. J Electron Commer Res 4(2):49–64
Dodds WB (1991) In search of value: how price and store name information influence buyers’ product perceptions. J. Consum Mark 8(2):15–24
Ludwig SA, Pulimi V, Hnativ A (2009) Fuzzy approach for the evaluation of trust and reputation of services. In: Proceedings of the 18th international conference on fuzzy systems (FUZZ-IEEE’09)
Nafi KW, Kar TS, Hossain M, Hashem MMA (2013) A fuzzy logic based certain trust model for E-commerce. In: 2013 International Conference on Informatics, Electronics & Vision (ICIEV), IEEE, pp 1–6
Nafi KW, Hossain A, Hashem MM (2013) An advanced certain trust model using fuzzy logic and probabilistic logic theory
Ba Sulin (2001) Establishing online trust through a community responsibility system. Decis Support Syst 31(3):323–336
Jøsang A, Ismail R, Boyd C (2007) A survey of trust and reputation systems for online service provision. Decis Support Syst 43(2):618–644
Kracher B, Corritore CL, Wiedenbeck S (2005) A foundation for understanding online trust in electronic commerce. J Inf Commun Ethics Soc 3(3):131–141
Sabater J, Sierra C (2005) Review on computational trust and reputation models. Artif Intell Rev 24(1):33–60
Van der Heijden H, Verhagen T, Creemers M (2003) Understanding online purchase intentions: contributions from technology and trust perspectives. Eur J Inf Syst 12(1):41–48
Wang YD, Emurian HH (2005) An overview of online trust: concepts, elements, and implications. Comput Hum Behav 21(1):105–125
Yoon SJ (2002) The antecedents and consequences of trust in online-purchase decisions. J Interact Mark 16(2):47–63
Anurag B, Aggarwal S (2014) Fuzzy based trust model to evaluate and analyse trust in B2C E-Commerce. In: 2014 IEEE international advance computing conference (IACC), pp 1300, 1306, 21–22 Feb 2014. doi:10.1109/IAdCC.2014.6779515
Head M, Hassanein K (2002) Trust in e-Commerce: evaluating the impact of third-party seals. Q J Electron Commer 3(3):307–325
McCole P, Ramsey E, Williams J (2010) Trust considerations on attitudes towards online purchasing: the moderating effect of privacy and security concerns. J Bus Res 63(9–10):1018–1024
Rashad Y, Abu Tabik MAS, Seyedi AP (2011) Security and trust in electronic commerce-finding the safe side. In: Information communication and management–international proceedings of computer science and information technology (2011)
Pennanen K, Kaapu T, Paakki M-K (2006) Trust, risk, privacy, and security in ecommerce. In: Proceedings of the ICEBÂ +Â eBRF Conference, 2006
Ganguly B et al (2010) The effects of website design on purchase intention in online shopping: the mediating role of trust and the moderating role of culture. Int J Electro Bus 8(4):302–330
Cheskin Research and Studio Archetype Deliver E-Commerce Trust Study (1999). The Free Library. Research and Studio Archetype Deliver E-Commerce Trust Study.-a053541794. http://www.thefreelibrary.com/Cheskin. Accessed 2 Apr 2014
Manchala DW (2000) E-commerce trust metrics and models. IEEE Internet Comput 4(2):36–44
Weisberg J, Te’eni D, Arman L (2011) Past purchase and intention to purchase in e-commerce: the mediation of social presence and trust. Internet Res 21(1):82–96
Smarandache F (1999) Linguistic paradoxists and tautologies, vol XIX. Libertas Mathematica, University of Texas at Arlington, Arlington, pp 143–154
Smarandache F (2002a) A unifying field in logics: neutrosophic logic, multiple-valued logic. Int J 8(3):385–438
Smarandache F (ed) (2002c) Proceedings of the first international conference on neutrosophy, neutrosophic logic, neutrosophic set, neutrosophic probability and statistics. University of New Mexico, Gallup Campus, Xiquan, Phoenix, 147 pp
Smarandache F (2002b) Neutrosophy, a new branch of philosophy, in multiple-valued logic. Int J 8(3):297–384
Smarandache F (2003) Definition of neutrosophic logic: a generalization of the intuitionistic fuzzy logic, In: Proceedings of the third conference of the european society for fuzzy logic and technology, EUSFLAT 2003, University of Applied Sciences at Zittau/Goerlitz, Zittau, Germany, pp 141–146, 10–12 Sept 2003
Wang L-X (1999) A course in fuzzy systems. Prentice-Hall Press, Upper Saddle River
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer India
About this chapter
Cite this chapter
Aggarwal, S., Bishnoi, A. (2016). Neutrosophic Trust Evaluation Model in B2C E-Commerce. In: Bhattacharyya, S., Dutta, P., Chakraborty, S. (eds) Hybrid Soft Computing Approaches. Studies in Computational Intelligence, vol 611. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2544-7_14
Download citation
DOI: https://doi.org/10.1007/978-81-322-2544-7_14
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2543-0
Online ISBN: 978-81-322-2544-7
eBook Packages: EngineeringEngineering (R0)