A fuzzy logic-based system for assessing the level of business-to-consumer (B2C) trust in electronic commerce Fahim Akhter a, * , Dave Hobbs b , Zakaria Maamar c a College of Information Systems, Zayed University, Box 19282, Dubai, UAE b University of Bradford, Bradford, West, Yorkshire, UK c Zayed University, Dubai, UAE Abstract The purpose of this paper is to present an application of fuzzy logic to human reasoning about electronic commerce (e-commerce) transactions. This paper uncovers some of the hidden relationships between critical factors such as security, familiarity, design, and competitiveness. We analyze the effect of these factors on human decision process and how they affect the Business-to-Consumer (B2C) outcome when they are used collectively. This research provides a toolset for B2C vendors to access and evaluate a user’s transaction decision process, and also an assisted reasoning tool for the online user. q 2005 Elsevier Ltd. All rights reserved. Keywords: Business-to-Consumer; e-commerce; Fuzzy logic 1. Introduction and motivation During online shopping, a user often relies on common sense and applies vague and ambiguous terms when making a buying decision. Online customer normally develops in his/her mind some sort of ambiguity, given the choice of similar alternative products and services (Mohanty & Bhasker, 2005). Decisions to buy or not to buy online are often based on users’ human intuitions common sense and experience, rather than on the availability of clear, concise and accurate data. Fuzzy logic is used for reasoning about inherently vague concepts (Lukasiewicz, 1970), such as ‘online shopping is convenient’, where level of convenience is open to interpretation. The purpose of this research is therefore to apply the fuzzy logic to human reasoning where we specifically focus on the reasoning processes behind e-commerce transactions. Fuzzy systems allow the encoding of knowledge in a form that can be used to reflect the way humans think about a complex problem such as online shopping. A human usually think in imprecise terms such as high and low, fast and slow, and heavy and light (Black, 1937). Fuzzy expert system model imprecise information, by attempting to capture knowledge in a similar fashion to the way in which it is considered to be represented in the human mind, and therefore improves cognitive modelling of a problem (Cox, 1994). As a result, fuzzy logic is leading to new and human- like, intelligent systems that might be used to understand the thought processes behind any B2C transactions. The rationale for using fuzzy logic systems to uncover vague decision process because it is well suited for modeling human decision-making. Human decision-making is com- plex, and can be based on simultaneous evaluation of many facets such as fear, experience, privacy, intuition and so forth. Though many factors influence the decision process of B2C transactions such as ease-of-use, pricing, convenience, and security (Akhter et al., 2003), the perception of an influencing feature is more important than the actual level of the feature itself. For example if the perceived security level is higher than its actual implementation then that will contribute positively to the level of B2C outcome. There may be cases where the reverse is true as well, but for such cases a high level of persuasion will be needed to alter the perception level. This research had adopted a fuzzy logic approach and utilized a mathematical research toolset 0957-4174/$ - see front matter q 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.eswa.2004.12.039 Expert Systems with Applications 28 (2005) 623–628 www.elsevier.com/locate/eswa * Corresponding author. Tel.: C97150 6743130; fax: C9714v2640854. E-mail addresses: fahim.akhter@zu.ac.ae (F. Akhter), d.hobbs@ bradford.ac.uk (D. Hobbs), zakaria.maamar@zu.ac.ae (Z. Maamar).