Closed-loop feedback computation model of dynamical reputation based on the local trust evaluation in business-to-consumer e-commerce

Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce

Decision making on adoption of cloud computing in e-commerce using fuzzy TOPSIS

© 2017 IEEE. Cloud computing promises enhanced scalability, flexibility, and cost-efficiency. In practice, however, there are many uncertainties about the usage of cloud computing resources in the e-commerce context. As e-commerce is dependent on a reliable and secure online store, it is important for decision makers to adopt an optimal cloud computing mode (Such as SaaS, PaaS and IaaS). This study assesses the factors associated with cloud-based e-commerce based on TOE (technological, organizational, and environmental) framework using multi-criteria decision-making technique (Fuzzy TOPSIS). The results show that Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) approach proposes software-as-a-service (SaaS) as the best choice for e-commerce business

A Two-Staged SEM-AHP Technique for Understanding and Prioritizing Mobile Financial Services Perspective Adoption

The development of wireless and mobile technologies has offered a remarkable business opportunity for mobile financial services (MFS). This research focuses on predicting and prioritizing MFS perspective adoption through multi-dimensional consumers’ trust and perceived risk factors concurrently, which concepts found scant in the literature. An integrated technique based on survey questionnaire was suggested whereby the theoretical model was tested employing structural equation modeling (SEM), and the SEM output generated were utilized as inputs for analytic hierarchy process (AHP) to rank MFS perspective. Several antecedents of trust and perceived risk were identified and confirmed. However, perceived time risk has no statistically significant influence on aggregate perceived risk. The findings indicated that dispositional trust and perceived privacy risk impact consumers more than do other precursors of trust and perceived risk respectively. Consumers rely on these two factors probably because they are quite related to consumer personality trait and relevant to services provided. Mobile money transfer is the preferable MFS perspective used in Togo followed by mobile payment, and mobile banking correspondingly based on AHP result. The outcomes underscore that MFS managers require adopting and build trust-risk base in strategically crucial information system when formulating strategies to attract the ever-larger consumer. This study as well offered an innovative new approach to comprehend MFS adoption perspective through the benchmark methodology provided. Keywords: Mobile financial services adoption, SEM (Structural Equation Modeling), AHP (Analytic Hierarchy Process), Multi-analytic approach, Trust, Perceived risk, User behavio

INVESTIGATION OF THE ROLE OF SERVICE LEVEL AGREEMENTS IN WEB SERVICE QUALITY

Context/Background: Use of Service Level Agreements (SLAs) is crucial to provide the value added services to consumers to achieve their requirements successfully. SLAs also ensure the expected Quality of Service to consumers. Aim: This study investigates how efficient structural representation and management of SLAs can help to ensure the Quality of Service (QoS) in Web services during Web service composition. Method: Existing specifications and structures for SLAs for Web services do not fully formalize and provide support for different automatic and dynamic behavioral aspects needed for QoS calculation. This study addresses the issues on how to formalize and document the structures of SLAs for better service utilization and improved QoS results. The Service Oriented Architecture (SOA) is extended in this study with addition of an SLAAgent, which helps to automate the QoS calculation using Fuzzy Inference Systems, service discovery, service selection, SLA monitoring and management during service composition with the help of structured SLA documents. Results: The proposed framework improves the ways of how to structure, manage and monitor SLAs during Web service composition to achieve the better Quality of Service effectively and efficiently. Conclusions: To deal with different types of computational requirements the automation of SLAs is a challenge during Web service composition. This study shows the significance of the SLAs for better QoS during composition of services in SOA

Applying MCDM Technique in analyzing the effect of promotion items based on online shopping factors : a case study

Developing technology causes companies in a market to compete with each other in challenging ways. In addition to a holistic marketing concept which focuses on the needs of target markets and delivering superior value, marketing should be adapted with new technology to fulfill consumer needs. Although many strategies have been introduced for marketing, digital marketing or marketing 4.0 is a new generation of marketing that engages with the audience through digital tools. These days, online shopping is only too popular among consumers. Many factors which affect customer decision during online shopping have been explored. In this paper, the effect of promotion items in online shopping will be explained. The main aim of this paper is to apply a multi-criteria decision-making technique in prioritizing eleven promotion items by considering five online customer shopping criteria. The novelty of this paper is to apply PROMETHEE II (Preference Ranking Organization METHod for Enrichment of Evaluations) in analyzing the effect of promotion items based on online shopping criteria. PROMETHEE II completely prioritizes discrete alternatives. A case study is conducted in a home appliance company in Iran

An Intelligent Customer Relationship Management (I-CRM) Framework and its Analytical Approaches to the Logistics Industry

This thesis develops a new Intelligent Customer Relationship Management (i-CRM) framework, incorporating an i-CRM analytical methodology including text-mining, type mapping, liner, non-liner and neuron-fuzzy approaches to handle customer complaints, identify key customers in the context of business values, define problem significance and issues impact factors, coupled with i-CRM recommendations to help organizations to achieve customer satisfaction through transformation of the customer complaints to organizational opportunities and business development strategies

MULTIMOORA under Interval-Valued Neutrosophic Sets as the Basis for the Quantitative Heuristic Evaluation Methodology HEBIN

During the last decade, researchers put a lot of effort into the development of the multi-criteria decision methods (MCDM) capable of dealing with the uncertainty and vagueness of the initial information. MCDM approaches that work under the environment of the interval-valued neutrosophic sets (IVNS) demonstrate credibility for the analysis of different opinions as well as for the inconsistency of the criteria evaluation data. The novel multicriteria decision-making approach MULTIMOORA-IVNS (multi-objective optimisation by ratio analysis under interval-valued neutrosophic sets) is presented in this paper. A novel heuristic evaluation methodology HEBIN (heuristic evaluation based on interval numbers) that exploits MULTIMOORA-IVNS for the processing of the evaluation results is also presented in this research. HEBIN is able to increase the accuracy of the checklists-based heuristic evaluation and to diminish the impact of the inconsistencies caused by the evaluators. A comparison of six e-commerce websites is introduced to reveal the practicalities of the proposed multicriteria decision-making application.This article belongs to the Special Issue Multiple Criteria Decision Makin