Abstract: Web applications have become complex and crucial for many firms, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering). The scientific community has focused attention to Web application design, development, analysis, testing, by studying and proposing methodologies and tools. Static and dynamic techniques may be used to analyze existing Web applications. The use of traditional static source code analysis may be very difficult, for the presence of dynamically generated code, and for the multi-language nature of the Web. Dynamic analysis may be useful, but it has an intrinsic limitation, the low number of program executions used to extract information. Our reverse engineering analysis, used into our WAAT (Web Applications Analysis and Testing) project, applies mutational techniques in order to exploit server side execution engines to accomplish part of the dynamic analysis. This paper studies the effects of mutation source code analysis applied to Web software to build application models. Mutation-based generated models may contain more information then necessary, so we need a pruning mechanism.
Abstract: A generalised relational data model is formalised for
the representation of data with nested structure of arbitrary depth. A
recursive algebra for the proposed model is presented. All the
operations are formally defined. The proposed model is proved to be
a superset of the conventional relational model (CRM). The
functionality and validity of the model is shown by a prototype
implementation that has been undertaken in the functional
programming language Miranda.
Abstract: Many firms implemented various initiatives such as outsourced manufacturing which could make a supply chain (SC) more vulnerable to various types of disruptions. So managing risk has become a critical component of SC management. Different types of SC vulnerability management methodologies have been proposed for managing SC risk, most offer only point-based solutions that deal with a limited set of risks. This research aims to reinforce SC risk management by proposing an integrated approach. SC risks are identified and a risk index classification structure is created. Then we develop a SC risk assessment approach based on the analytic network process (ANP) and the VIKOR methods under the fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy numbers. By using FANP, risks weights are calculated and then inserted to the FVIKOR to rank the SC members and find the most risky partner.
Abstract: This paper aims at a new challenge of customer
satisfaction on mobile customer relationship management. In this
paper presents a conceptualization of mCRM on its unique
characteristics of customer satisfaction. Also, this paper develops an
empirical framework in conception of customer satisfaction in
mCRM. A single-case study is applied as the methodology. In order to
gain an overall view of the empirical case, this paper accesses to
invisible and important information of company in this investigation.
Interview is the key data source form the main informants of the
company through which the issues are identified and the proposed
framework is built. It supports the development of customer
satisfaction in mCRM; links this theoretical framework into practice;
and provides the direction for future research. Therefore, this paper is
very useful for the industries as it helps them to understand how
customer satisfaction changes the mCRM structure and increase the
business competitive advantage. Finally, this paper provides a
contribution in practice by linking a theoretical framework in
conception of customer satisfaction in mCRM for companies to a
practical real case.
Abstract: In the era of great competition, understanding and satisfying
customers- requirements are the critical tasks for a company
to make a profits. Customer relationship management (CRM) thus
becomes an important business issue at present. With the help of
the data mining techniques, the manager can explore and analyze
from a large quantity of data to discover meaningful patterns and
rules. Among all methods, well-known association rule is most
commonly seen. This paper is based on Apriori algorithm and uses
genetic algorithms combining a data mining method to discover fuzzy
classification rules. The mined results can be applied in CRM to
help decision marker make correct business decisions for marketing
strategies.
Abstract: Modern information and communication technologies
offer a variety of support options for the efficient handling of
customer relationships. CRM systems have been developed, which
are designed to support the processes in the areas of marketing, sales
and service. Along with technological progress, CRM systems are
constantly changing, i.e. the systems are continually enhanced by
new functions. However, not all functions are suitable for every
company because of different frameworks and business processes. In
this context the question arises whether or not CRM systems are
widely used in Austrian companies and which business processes are
most frequently supported by CRM systems. This paper aims to shed
light on the popularity of CRM systems in Austrian companies in
general and the use of different functions to support their daily
business. First of all, the paper provides a theoretical overview of the
structure of modern CRM systems and proposes a categorization of
currently available software functionality for collaborative,
operational and analytical CRM processes, which provides the
theoretical background for the empirical study. Apart from these
theoretical considerations, the paper presents the empirical results of
a field survey on the use of CRM systems in Austrian companies and
analyzes its findings.
Abstract: After reporting a literature review on Customer
Relationship Management (CRM) and knowledge management, some
important issued arise, in particular related to the lack of success of
CRM strategies implementation. The paper contributes to this
proposing an integrated model of CRM success taking into account
complementary factors such as organizational factors, technology,
knowledge management and customer orientation.
Abstract: This paper investigates the relationship between different dimensions of customer relationship management and innovation capabilities in Melli Bank of Iran. Five dimensions of CRM include information sharing, customer involvement, long-term partnership, joint problem solving and technology-based CRM are selected to measure their relationship with innovation capabilities including innovation in product, innovation in process, innovation in administrative affairs, innovation in marketing, and finally innovation in services. Research findings indicate that there is significant relationship between CRM dimensions and innovation capabilities in Melli bank of Iran.