Cost and Benefit Analysis for E-Service Applications

Companies are adopting Internet-based electronic services (E-services) attracting customers, sharing of business information, maintaining business relationships and conducting business transactions. Companies in the earlier stages of employing E-services have little information and knowledge on its potential organizational and relational impacts. Through few years practice of E-services, companies have obtained related knowledge. They urgently need to assess the costs to move service online against the benefits received via adopting E-service, and identify the impact of E-service adoption in companies’ relationships with their customers as a result of innovative use of E-services. The initial objective of the research is to explore the relationships between cost factors, benefit factors and customer satisfaction for an E-service application. A further objective is to find a potential path for developing a customer oriented E-service application from its current implementation through identifying the types of changes taking place in the service functions and operations as a result of increased use of E-services. Though conducting a survey, this paper, as a stage report of the project, presents a research framework for E-service evaluation, identifies main cost and benefit factors of E-service and analyses the relationships between these factors. Finally, a cost benefit relationship model is proposed

A Group Decision Making Approach for Dealing with Fuzziness in Decision Process

In order to deal with various imprecise opinions and preferences of decision makers in group decision-making process, this paper proposes a fuzzy group decision-making approach. The approach has three advantages from existing approaches. First, it can handle simultaneously group members’ fuzzy preferences for alternative solutions, fuzzy judgments for solution selection criteria and fuzzy weights for their roles in group decision-making to arrive a group consensus decision. Second, it allows group members to generate selection criteria for the best solution rather than assume them to be given before a group meeting. The third is that it uses general fuzzy number to express linguistic terms which is used to describe the fuzziness of individual preferences, judgments and weights in group decision-making. It therefore accepts any forms of fuzzy number, including triangular fuzzy number, rectangle fuzzy number and continuous fuzzy number, when applying the group decision-making approach

A New Approximate Algorithm for Solving Multiple Objective Linear Programming with Fuzzy Parameters

Many business decisions can be modeled as multiple objective linear programming (MOLP) problems. When formulating a MOLP problem, objective functions and constraints involve many parameters which possible values are assigned by the experts who are often imprecisely or ambiguously known. So, it would be certainly more appropriate to interpret the experts’ understanding of the parameters as fuzzy numerical data which can be represented by fuzzy numbers. This paper focuses on fuzzy multiple objective linear programming (FMOLP) problems with fuzzy parameters in any form of membership function in both objective functions and constraints. Based on the related results of fuzzy linear programming (FLP) and linear programming problems with fuzzy equality and inequality constraints proposed by Zhang et al, this paper firstly proposes related definitions and concepts about FMOLP problems with fuzzy parameters. It then proposes a new approximate algorithm developed for solving the corresponding MOLP problems and the FMOLP problems. Finally, the use of related concepts, theorems, and the proposed approximate algorithm is illustrated by an example involving different cases which include setting various iterate steps, tolerances, weights, and satisfaction levels

The resilience of interdependent transportation networks under targeted attack

Modern world builds on the resilience of interdependent infrastructures characterized as complex networks. Recently, a framework for analysis of interdependent networks has been developed to explain the mechanism of resilience in interdependent networks. Here we extend this interdependent network model by considering flows in the networks and study the system's resilience under different attack strategies. In our model, nodes may fail due to either overload or loss of interdependency. Under the interaction between these two failure mechanisms, it is shown that interdependent scale-free networks show extreme vulnerability. The resilience of interdependent SF networks is found in our simulation much smaller than single SF network or interdependent SF networks without flows.Comment: 5 pages, 4 figure