Alireza Faed

A methodology to map customer complaints and measure customer satisfaction and loyalty

In this study, an analysis was conducted for the relationships between the main components of customer relationship management (CRM) and customer complaints in the domain of logistics and transport. Today, complaints and the handling of complaints play a pivotal role in customer relationships. Moreover, companies are reluctant to admit that they have difficulties with customers’ complaints, but as yet there appears to be no complete solution to this issue. To remedy this situation, customer complaints must be comprehensively collected and analysed. Issues must be classified, and timely solutions must be developed. In this paper, a conceptual framework is proposed including mathematical models, hypothesised relationships, perceived value and interactivity between customer, business and the system, as well as customer satisfaction analytics. The framework will address the relationship between customer satisfaction issues, loyalty and customer acquisition and estimate customer satisfaction and loyalty. For the purpose of analysis, this study uses both qualitative and quantitative approaches. For data collection, a survey questionnaire was distributed to 60 Fremantle Port logistics and transport customers. For the quantitative approach, linear and nonlinear modelling is adopted. Using the model, we are able to address the shortcomings of CRM technology, and tackle the issues of loyalty improvement and customer acquisition. Finally, based on nonlinear modelling and using a fuzzy inference system, namely the Takagi–Sugeno-type approach, we defined fuzzy rules, by means of which we ascertain the relationship between customer satisfaction and the main relevant variables.

The Critical Success Factors for Implementation of CRM and Knowledge Management in a Work Setting

Customer Relationship Management is the most vigorous tools in our era and is the integration of trust, business and technology to gratify the requirements of the clients. CRM is a strategy of dealing with people, technology and process and need to be implemented precisely. CRM is the most outstanding business strategy that consolidates internal procedures and externals to generate and convey value to the spotted customers and CRM can easily neutralize competitive perils, provide a good source of roadmap for the company and customers. Moreover it may clarify the potential pitfalls in creating success for the company. CRM involves validating and evaluating critical success factors, which cover the three perspectives of CRM as the theoretical base, and which constitute a guide for companies in the implementation of the applications. Due to this, the desired benefits have intensified customer satisfaction and maintenance, by generating personalized products and value-added services. In this paper, the author investigates the factors that can positively leverage the implementation and use of CRM and creates differentiation among these factors and knowledge management factors. What is more, the paper aims at determining technical feature between CRM and knowledge management and managed to compare KM with CRM successfully.

Intelligent CRM on the Cloud

This paper presents a new conceptual framework and practical solution for Customer Relationship Management (CRM) and E-Loyalty programs for cutting edge M-Commerce. CRM has come to the world of technology to help companies maximise technology usage. CRM means disciplined business strategy to create and sustain long-term, profitable customer relationships. To this aim, it must concentrate on customer. This paper introduces the notion of Intelligence CRM (i-CRM), and will define and develop i-CRM, E-Loyalty for the M-Commerce environment including Cloud services. The conceptual framework will include solutions for customer complaints and evaluation of the solution through perceived value, interactivity, and acceptance of i-CRM, perceived ease of use, perceived usefulness, loyalty and E-Loyalty. This paper shows how i-CRM can foresee the threshold of customer feedback creating an innovative solution to minimize negative customer feedback and increase the loyalty and E-Loyalty of an organization.

The efficient bond among mobile commerce, CRM and E-loyalty to maximise the productivity of companies

Mobile commerce, has become a significant topic in IS research community and it is a key concept for many businesses, However, it has not fulfilled the expectations. This paper tackles the issue of mobile commerce in three different ways. First, it emphasizes the relative importance of customer relationship management and its relationship with mobile commerce. Second, it illustrates the ways to enhance E-loyalty of the clients within small and medium enterprises. Ultimately, the positive relationship among these, three concepts will be clarified. M-Commerce constitutes an important future market worldwide. This paper argues that businesses should strengthen and enhance loyalty as well as e-loyalty and M-Commerce activities, in order to better acquire the customers toward wireless marketing and customer relationship channels. Moreover to get the most euphoria businesses must create value for consumers in a way that is different from what they get used to prior to the latest version of services from the businesses. This paper, introduces a new area of doing business with the assistance of CRM and some evaluators to grasp loyalty under the context of mobile commerce. In addition, businesses should consider consumers willingness to use successful features of M-Commerce. While performing the project, we expect to achieve productivity and reputation to the organization.

A conceptual model for interactivity, complaint and expectation for CRM

Interactivity is crucial for Customer Relationship Management (CRM). Shifting the level of interactivity may transform dysfunctional CRM and marketing systems to a more effective formula and create a lasting relationship between customers and the company. In this paper we explore various aspects of interactivity such as modes, means and mediums of interactivity and their relationship with complaint and expectation. We propose two hypotheses to quantitatively formalize the relationships. We briefly discuss the managerial implications. In our future work, rigorous statistical analysis will be carried out to validate our hypotheses.

Linear Modelling and Optimization to Evaluate Customer Satisfaction and Loyalty

In this study, a conceptual framework is postulated to mathematically evaluate and ascertain the hypothesised relationship that perceived value and interactivity has with customer dissatisfaction issues. Then, the relationship between customer satisfaction issues and loyalty and customer acquisition, will be tested to enhance customer satisfaction and loyalty. For the qualitative part of the research, an interview survey was conducted of 40 employees at the Fremantle port of Western Australia and the collected data was analysed using NVivo. In the second data collection phase, a survey questionnaire was distributed to 60 port customers. Using data envelopment analysis (DEA), the important and most important customers were selected from the sample. In the final stage, utilising linear modelling, a positive association between the variables was established. Our results illustrated that all of the antecedents and consequences of customer satisfaction issues positively affect the issues. All of the activities were conducted under i-CRM control.

Analysis of digital DSP blocks using GDI technology

In parallel with enhancements in the technology of integrated circuits, transistors are implemented in silicon. Though the price is reduced; design is more complicated, which create the efficiency and power consumption. The reason why modern GDI-based circuit is the focus of attention is that in designing digital circuit, less power is required while more efficiency is obtained. Lowering the complexity of logic circuit can bring about reduction of power consumption, propagation delay and decrease circuit space. GDI-based integrated circuit resembles MOSFET transistors but have fewer transistors and higher performance capability. This study addresses two main areas which are Studying and investigating primary logic gate behaviors of NOR, NAND, OR, NOR, XOR, XNOR, INVERTER, that are used to employ CMOS, NMOS and GDI. Moreover, designing and analysis of FIR block which are done, using basic blocks implemented in the first stage. In this study, the design circuits-either basic blocks or FIR will be compared to NMOS and CMOS in terms of average power consumption, performance, and area occupancy.

Track I: Fuzzy semantic computing in digital ecosystems

Semantic computing deals with semantic information from texts such as structured data, video, audio, written content, etc. Because of the structure of fuzzy logic, it is suitable for a semantic computing technique environment. Fuzzy semantic computing is also a suitable technique that can strengthen ICT to support different digital ecosystems.

Analytical Text Mining in I-CRM for Customer Complaint Analysis

This chapter provides details of the interviews collected, and their subsequent categorisation and analysis using the text-mining tool. Several advanced concepts used in text mining analysis are defined, followed by qualitative data analysis. Issues are identified in detail and a scientific approach is presented to justify the issues identified as being those relevant to the port in terms of logistics and transport.

Improving Customer Satisfaction Through Customer Type Mapping and I-CRM Strategies

In this chapter, we carry out the modelling of dissatisfaction and satisfaction through the five steps of customer screening, data reduction, principal component analysis, data envelopment analysis, achieving potential improvement and providing recommendations in order to address the issues at the Fremantle port. We also re-validate our hypotheses for the major variables using a complete methodology. This process will help us to group our customers into clusters and we map the issues and the impact factors to these clusters. This in turn helps us to identify and prioritise the significant issues that should be addressed first in order to improve customer satisfaction within the shortest time with maximum results. This concept can be proven by the processes of analytical hierarchy and sensitivity analysis which provide mapping between customer type and satisfaction level.