Evaluation of Fuzzy Models to Support Online-Trust Assessment

2010 ◽  
pp. 90-100
Author(s):  
Fahim Akhter ◽  
Zakaria Maamar
Keyword(s):  
Fuzzy Logic ◽  
Electronic Commerce ◽  
Critical Element ◽  
Face To Face ◽  
Online Trust ◽  
Fuzzy Models ◽  
Trust Models

Online trust is a critical element to the success of electronic commerce (e-commerce). Indeed it reduces the level of uncertainty that arises because of the lack of face-to-face interactions with vendors. In ecommerce purchaser-vendor interactions are subject to uncertainty, anonymity, and communication means reliability. This chapter discusses how some trust models have been developed to address these issues. Some models promote familiarity and competitiveness as part of the exercise of assessing online trust. This assessment uses fuzzy logic-based techniques.

FUZZY DYNAMIC LOGIC

2006 ◽  
Vol 02 (01) ◽  
pp. 43-55 ◽  
Author(s):  
LEONID I. PERLOVSKY
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Logic ◽  
Learning System ◽  
Dynamic Adaptation ◽  
Fuzzy Models ◽  
Uncertain Knowledge ◽  
Model Improvement ◽  
The Mind ◽  
Fuzzy State ◽  
Theory Of Forms

Fuzzy logic is extended toward dynamic adaptation of the degree of fuzziness. The motivation is to explain the process of learning as a joint model improvement and fuzziness reduction. A learning system with fuzzy models is introduced. Initially, the system is in a highly fuzzy state of uncertain knowledge, and it dynamically evolves into a low-fuzzy state of certain knowledge. We present an image recognition example of patterns below clutter. The paper discusses relationships to formal logic, fuzzy logic, complexity and draws tentative connections to Aristotelian theory of forms and working of the mind.

scholarly journals An Application Expert System for Evaluating Effective Factors on Trust in B2C WebsitesTrust, Security, ANFIS, Fuzzy Logic, Rule Based Systems, Electronic Commerce

Engineering ◽  
2011 ◽  
Vol 03 (11) ◽  
pp. 1063-1071 ◽  
Author(s):  
Mehrbakhsh Nilashi ◽  
Karamollah Bagherifard ◽  
Othman Ibrahim ◽  
Nasim Janahmadi ◽  
Mousa Barisami
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Electronic Commerce ◽  
Rule Based ◽  
Effective Factors ◽  
Logic Rule ◽  
Rule Based Systems

A Fuzzy Logic-Based Approach for Supporting Decision-Making Process in B2C Electronic Commerce Transaction

2011 ◽  
pp. 1416-1429
Author(s):  
Fahim Akhter ◽  
Zakaria Maamar ◽  
Dave Hobbs
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Electronic Commerce ◽  
Decision Process ◽  
Human Reasoning ◽  
Critical Factors ◽  
Human Decision Process ◽  
Human Decision ◽  
Business To Consumer ◽  
B2c Electronic Commerce

The purpose of this article is to present an application of fuzzy logic to human reasoning about electronic commerce (e-commerce) transactions. This article 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.

B2B Website Benefits Realization in Australian SMEs

2010 ◽  
pp. 106-114
Author(s):  
Chad Lin ◽  
Yu-An Huang ◽  
Rosemary Stockdale
Keyword(s):  
Electronic Commerce ◽  
Critical Element ◽  
Business Growth ◽  
Potential Barriers ◽  
Evaluation Practices ◽  
Successful Design ◽  
Benefits Realization ◽  
Potential Customers

One aspect of small and medium-sized enterprises (SMEs) electronic commerce activity that is acknowledged but rarely examined is their use of websites as they are a critical element of their business growth and competitiveness (Loiacono et al., 2002). Their successful design and use can alter the effectiveness of an SME’s venture into electronic commerce. However, SMEs are still lagging behind larger organizations in the adoption and evaluation of their electronic commerce activities despite the benefits it offers (Lin et al., 2007) and in overcoming the potential barriers that hamper their evaluation practices (Standing and Lin, 2007). Understanding the factors used by the SMEs’ potential customers to evaluate their website effectiveness can serve as a basis for creating and improving websites (Simmons et al., 2007).

Trust in Electronic Commerce

2010 ◽  
pp. 65-74 ◽  
Author(s):  
Hongwei Du ◽  
Albert Lederer ◽  
Jiming Wu
Keyword(s):  
World Wide Web ◽  
Electronic Commerce ◽  
World Wide ◽  
The Internet ◽  
Face To Face ◽  
The Past ◽  
Internet Users ◽  
Market Research Company ◽  
Research Company ◽  
Online Shoppers

In the past two decades, electronic commerce has been growing rapidly due to the increasing popularization of personal computers, expanding penetration of broadband, and continuing development of the Internet and World Wide Web. According to eMarketer (2009), an e-business and online market research company, the total U.S. e-commerce sales (excluding travel) will grow from $127.7 billion in 2007 to $182.5 billion in 2010. The firm also estimates that the number of online shoppers in U.S. will increase from 131.1 million—nearly four-fifths of Internet users—by the year 2007, to 148.7 million by the year 2010. The growth of e-commerce relies not only on the great convenience of conducting transactions over the Internet but also on consumers’ willingness to trust an online merchant. This view is consistent with that advanced by Holsapple and Wu (2008): non-face-to-face, Internet-based transactions require an element of trust; in other words, trust is a foundation of e-commerce.

A Fuzzy Logic-Based Approach for Supporting Decision-Making Process in B2C Electronic Commerce Transaction

2009 ◽  
pp. 258-271
Author(s):  
Fahim Akhter ◽  
Zakaria Maamar ◽  
Dave Hobbs
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Electronic Commerce ◽  
Decision Process ◽  
Human Reasoning ◽  
Critical Factors ◽  
Human Decision Process ◽  
Human Decision ◽  
Business To Consumer ◽  
B2c Electronic Commerce

The purpose of this article is to present an application of fuzzy logic to human reasoning about electronic commerce (e-commerce) transactions. This article 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.

scholarly journals ANALYZING ECONOMIC STRUCTURE AND COMPARING THE RESULTS OF THE PREDICTED ECONOMIC GROWTH BASED ON SOLOW, FUZZY-LOGIC AND NEURAL-FUZZY MODELS

2011 ◽  
Vol 17 (1) ◽  
pp. 101-115 ◽  
Author(s):  
Mirnaser Mirbagheri ◽  
Namiq Tagiev
Keyword(s):  
Economic Growth ◽  
Fuzzy Logic ◽  
Variable Coefficients ◽  
Supply Side ◽  
Economic Growth Rate ◽  
Fuzzy Models ◽  
Investigation Period ◽  
Neural Fuzzy ◽  
Better Than

Investigating the factors effective on economic growth is of great importance for most economists. Although lots of studies have been done on economic growth in the world, it has less been regarded in Iran. In this article, by estimating growth regression, we attempt to investigate the supply side of economic growth in Iran. Then we compare the predictive results of Fuzzy-logic, Neural-Fuzzy and Solow models. The results show that there was negative significant relationship (i.e.–0.035) between unstable policy and economic growth rate in Iran during investigation period (1959–2001). In this model, the effect of expenses used by government is positive (i.e. 0.01). Furthermore, the estimated results of long term relationship show that the variable coefficients of capital, labor power, exportation, and inflation are 0.319, 0.016, 0.001, and–0.001, respectively. And also by comparing the predictive results of models for the average percent of annual growth, it is predicted that the average percent of Solow, Neural-Fuzzy, and Fuzzy-logic models are 7.17%, 5.92%, and 6.46% for 2002–2006, respectively. Evaluation of results from the models on the basis of criteria shows that model Neural-Fuzzy predicts better than Fuzzy-logic and Solow models. In other words, forecasting by the model Neural-Fuzzy is recommended.

scholarly journals The improvement of the method for developing the knowledge data base for the intelligent support system of decision making on the Fuzzy Logic principles

2018 ◽  
pp. 26-41
Author(s):  
V. B. Kropyvnytska ◽  
O. V. Yefremov ◽  
H. N. Sementsov
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Data Base ◽  
Support System ◽  
Fuzzy Simulation ◽  
Automated Control ◽  
Intelligent Support ◽  
Fuzzy Models

The article deals with the issue of Fuzzy-simulation of controllers for solving practical problems of automated control. The peculiarities of Fuzzy-simulation of cascade controllers in the Matlab environment are studied. The presentation is accompanied by examples of the development of individual Fuzzy models and an illustration of conducting all necessary operations with fuzzy sets.

A foundation for understanding online trust in electronic commerce

2005 ◽  
Vol 3 (3) ◽  
pp. 131-141 ◽  
Author(s):  
Beverly Kracher ◽  
Cynthia L. Corritore ◽  
Susan Wiedenbeck
Keyword(s):  
Electronic Commerce ◽  
Online Trust

Role of Platform, Supplier and Medium in Online Trust Formation

2019 ◽  
Vol 15 (1) ◽  
pp. 58-70
Author(s):  
You Yan ◽  
Zhao Dongmei ◽  
Yang Weining
Keyword(s):  
Electronic Commerce ◽  
Structural Equation ◽  
Negative Impact ◽  
Positive Impact ◽  
Web Design ◽  
Trust Model ◽  
Equation Modeling ◽  
Online Platform ◽  
Online Trust

Research literature suggests that online trust and commitment are the core constructs in building a sustainable electronic commerce relationship. This article investigates the respective roles of the platform, supplier and medium in forming online trust, and determines whether these factors ultimately influence purchase intentions. It seeks to re-examine the trust model by McKnight and identifies how a trust model can be adapted in current business environments. A model is developed and tested by six constructs which have an impact on each other. Survey data from online platform customers (n = 386) are used to test the online trust hypotheses with structural equation modeling. As hypothesized, the results suggest that platform, supplier and medium have a positive relationship with online trust, and especially the platform has the highest positive impact. Among platform sub constructs, the web design, supplier rank and the privacy policy are crucial. After sale service, the company location and price strongly influence the supplier. For the medium sub constructs, 3rd party seals impact the medium more strongly than expert comments and consumer reviews. However, the medium has negative impact on behavioral intentions. The article identifies interesting differences between the original work by McKnight and the findings of this study, but basically concludes that the online trust theory applies to current electronic commerce market. Few studies have examined the role of platform, supplier and medium separately in forming online trust. This study divides platform and supplier into two separate constructs to meet the new market development. The modified model truly reflects the vibrant online platform environment and can provide better insight into managing the platform.

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