A robust methodology for prediction of trust and reputation values

In this paper, we present the FC direct trust value-based decision making methodology, for making direct trust value based decisions regarding interactions in (a) a given context and during the current time slot, and (b) a given context and at a future time slot. The direct trust value-based decision making methodology models the context specific nature of trust and the dynamic nature of trust to make direct trust value-based decisions regarding interactions. Additionally in this paper, we present the FC reputation-based trust decision making methodology, for making reputation-based trust decisions regard ing interactions, if direct trust value-based decisions cannot be made. The FC reputationbased trust decision making methodology can make reputationbased trust decisions regarding interactions in (a) a given context and during the current time slot, and (b) a given context and at a future time slot

Towards multi-criteria cloud service selection

Cloud computing despite being in an early stage of adoption is becoming a popular choice for businesses to replace in-house IT infrastructure due to its technological advantages such as elastic computing and cost benefits resulting from pay-as-you-go pricing and economy of scale. These factors have led to a rapid increase in both the number of cloud vendors and services on offer. Given that cloud services could be characterized using multiple criteria (cost, pricing policy, performance etc.) it is important to have a methodology for selecting cloud services based on multiple criteria. Additionally, the end user requirements might map to different criteria of the cloud services. This diversity in services and the number of available options have complicated the process of service and vendor selection for prospective cloud users and there is a need for a comprehensive methodology for cloud service selection. The existing research literature in cloud service selection is mostly concerned with comparison between similar services based on cost or performance benchmarks. In this paper we discuss and formalize the issue of cloud service selection in general and propose a multi-criteria cloud service selection methodology

Optimizing trust prediction in digital business ecosystem

The process of predicting the future trust value of an entity, based on its past value is a challenging issue. The prediction process is even more imperative in the scenario where in the interaction would take place at a future point in time. Being able to determine the confidence value of the predicted trust value is of prime importance to enable optimized trust prediction. In this paper we propose a set of metrics for determining the confidence level in the predicted trust value

Transactional risk-based decision making system in e-business interactions

The credit crunch and economic crisis have demonstrated the need to properly understand, characterize and assimilate risk in business activities. Failure to do this has resulted in serious consequences to the users involved. So the analysis and management of risk is one of the important pre-requisites to ensure a successful outcome in a business activity in any domain. In this paper we propose an approach by which an interaction initiating user in the domain of e-business ascertains beforehand the level of transactional risk in the successful completion of its business activity and utilizes it to determine on an interaction. The proposed model considers the different sub-categories and characteristics of transactional risk and ascertains in numeric and semantic terms the different levels and severities of its occurrence. It then utilizes the determined analysis of transactional risk to recommend on an informed interaction-based decision to the interaction initiating user

Highlighting the issues in making an informed interaction-based decision in industrial ecosystems

In the literature, the notion of trust has been widely discussed and various approaches have been proposed to assess and quantify it, in order to take it into consideration when making an interaction-based decision in industrial ecosystems. At the same time, the notion and importance of risk have been widely ignored and not been acknowledged as an important factor to consider, along with trust; while making an interaction-based decision. Although there are approaches in the literature which attempt to quantify risk in the domain of a business interaction in industrial ecosystems, none of them proposes a methodology by which the initiating agent of the interaction can ascertain and determine all the various concepts that are expressed by risk in that domain, and then utilize it to make an informed interaction-based decision. In this paper we present an evaluation of the approaches from the literature and highlight the issues which need to be addressed in order to assist the initiating agent of the interaction in making an informed interaction-based decision with another agent in Industrial ecosystems

Quantifying the numeric and linguistic magnitude of perceived risk in e-commerce interactions for RDSS

In an e-commerce business interaction, the risk assessing agent by analyzing the possible level of perceived risk beforehand can make an informed decision of its future course of interaction with an agent. The perceived risk in the context of an e-commerce business interaction is a multidimensional construct which is the combination of its subcategories. In this paper we propose a methodology by which the risk assessing agent can ascertain the numeric and linguistic level of perceived risk in an interadion by combining its different subcategories

Probabilistic assessment of financial risk in e-business associations

Business activities are a result of carefully formed associations between different users in order to achieve certain pre-decided outcomes. Decision-making in such associations is an important step and transactional risk analysis is one of the integral processes that facilitates this step. This paper presents an approach that determines the negative consequences (termed as financial risk) of forming e-business associations. Unlike other approaches, our model captures the different types of events and their uncertainties to determine the financial risk by using the convolution operator and expressing it as a probabilistic measure rather than as a crisp financial value. Such representation makes sense as the financial risk may be determined at a point of time in future where nothing is certain. Depending upon the complexity of the problem, we explain the different ways of using the convolution operator to determine the financial risk. The simulation result shows a better representation and understanding of the financial risk that will provide important inputs to the transactional risk analysis and the decision-making process

A methodology for transactional risk assessment and decision making in e-business interactions

The development and advancement of technologies have enabled users to complete their tasks efficiently. They have also provided them with various options and alternatives to complete and achieve their tasks. In such an environment, it is imperative for a user to make informed decisions that would ensure that its aims or objectives are achieved and its interaction experience is maximized. In the literature, various approaches for decision making have been proposed. But among those approaches, the notion of risk has been considerably ignored in the domain of e-business, despite its having been acknowledged as an important concept related to decision-making in any domain. In this paper, we propose a methodology by which users in an e-business domain can assess and analyze the level of transactional risk in the domain of e-business and then take it into consideration when making an informed interaction-based decision

Towards quantifying the possible risk in e-commerce interactions for RDSS

By analyzing the possible level of Risk beforehand the initiating agent can make an informed decision of its future course of interaction with an agent. The possible risk in the context of an e-commerce interaction is a multidimensional construct which is the combination of different constituents. In this paper we propose a methodology by which the initiating agent can determine and analyze those constituents in order to ascertain the possible level of risk in interacting with an agent

A fuzzy inference model for risk based informed decision-making in e-business

Since its invention, the web has considerably advanced and it now provides its users with sophisticated technologies and processes for facilitating interactions. This has enabled its users to complete their tasks by efficient ways, which reduces the duration of their interaction/s and in turn increases their productivity. But in such an environment, it is imperative for a user to make informed decisions in a proactive way by which it can achieve its aims and maximize its interaction experience. In the literature, various approaches have been proposed which a user can consider and utilize while making an interaction-based decision in web-based ecommerce. But at the same time the notion of risk has been considerably ignored in that domain; even though it has been mentioned in the literature that risk plays an important part while decision-making in any domain. So in order to have such an analysis of risk while decision-making, in this paper we highlight the importance of risk and then propose a fuzzy inference model for assisting risk-based decision making in e-commerce business interactions