An intelligent recommendation system framework for student relationship management

In order to enhance student satisfaction, many services have been provided in order to meet student needs. A recommendation system is a significant service which can be used to assist students in several ways. This paper proposes a conceptual framework of an Intelligent Recommendation System in order to support Student Relationship Management (SRM) for a Thai private university. This article proposed the system architecture of an Intelligent Recommendation System (IRS) which aims to assist students to choose an appropriate course for their studies. Moreover, this study intends to compare different data mining techniques in various recommendation systems and to determine appropriate algorithms for the proposed electronic Intelligent Recommendation System (IRS). The IRS also aims to support Student Relationship Management (SRM) in the university. The IRS has been designed using data mining and artificial intelligent techniques such as clustering, association rule and classification

Demand Response Strategy Based on Reinforcement Learning and Fuzzy Reasoning for Home Energy Management

As energy demand continues to increase, demand response (DR) programs in the electricity distribution grid are gaining momentum and their adoption is set to grow gradually over the years ahead. Demand response schemes seek to incentivise consumers to use green energy and reduce their electricity usage during peak periods which helps support grid balancing of supply-demand and generate revenue by selling surplus of energy back to the grid. This paper proposes an effective energy management system for residential demand response using Reinforcement Learning (RL) and Fuzzy Reasoning (FR). RL is considered as a model-free control strategy which learns from the interaction with its environment by performing actions and evaluating the results. The proposed algorithm considers human preference by directly integrating user feedback into its control logic using fuzzy reasoning as reward functions. Q-learning, a RL strategy based on a reward mechanism, is used to make optimal decisions to schedule the operation of smart home appliances by shifting controllable appliances from peak periods, when electricity prices are high, to off-peak hours, when electricity prices are lower without affecting the customer’s preferences. The proposed approach works with a single agent to control 14 household appliances and uses a reduced number of state-action pairs and fuzzy logic for rewards functions to evaluate an action taken for a certain state. The simulation results show that the proposed appliances scheduling approach can smooth the power consumption profile and minimise the electricity cost while considering user’s preferences, user’s feedbacks on each action taken and his/her preference settings. A user-interface is developed in MATLAB/Simulink for the Home Energy Management System (HEMS) to demonstrate the proposed DR scheme. The simulation tool includes features such as smart appliances, electricity pricing signals, smart meters, solar photovoltaic generation, battery energy storage, electric vehicle and grid supply.Peer reviewe

Applying FCM to Predict the Behaviour of Loyal Customers in the Mobile Telecommunications Industry

Using empirical data from the Kuwaiti mobile telecommunications sector, this study models a fuzzy cognitive map (FCM) to investigate the reciprocal effects of customer loyalty and its antecedents in an emerging market context. This study investigates the effect of perceived service quality, perceived service value and brand equity on customer loyalty and the simultaneous analysis of the reverse causality of these variables. Data pertaining to 350 subscribers were analysed. According to the results, the model reaches the equilibrium when brand equity and customer loyalty are increased and reach an optimal level. Based on these findings, the authors provide implications for managers in the mobile telecom industry

Agent based mobile negotiation for personalized pricing of last minute theatre tickets

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2012 Elsevier B.V.This paper proposes an agent based mobile negotiation framework for personalized pricing of last minutes theatre tickets whose values are dependent on the time remaining to the performance and the locations of potential customers. In particular, case based reasoning and fuzzy cognitive map techniques are adopted in the negotiation framework to identify the best initial offer zone and adopt multi criteria decision in the scoring function to evaluate offers. The proposed framework is tested via a computer simulation in which personalized pricing policy shows higher market performance than other policies therefore the validity of the proposed negotiation framework.The Ministry of Education, Science and Technology (Korea

The Fuzzy Decision Operations for Satisfying the Criteria of Customer Satisfaction

Customer relationship management (CRM) has emerged as a prominent aspect of business. In this respect, one of the notable developments of quality movement is an assessment of the customer satisfaction. The fuzzy rule based decision support system may be used as customer satisfaction rating system is useful where simple linear relationships do not subsist, where attribute evaluations are highly correlated and where some ability to make legal opinions in the context of the specific application is needed. In this paper, we are concentrating on the relationship between the costs of recharge coupon and talk time and validity and then analysis of consequence in the context of client satisfaction. So that at the base of this scheme we can select a profitable and customer satisfied recharge coupon of a mobile telecommunication company. This report introduces an approach to evaluate the character and reliability related customer satisfaction from recharge coupon and talk time data at each individual customer level and fuzzy logic will help us to resolve the customer satisfaction data. Finally a fuzzy logic approach is employed to construct the satisfaction model

Towards a business model for cellular network and telecommunication operators: a theoretical framework

Cellular networks and telecommunications bring major change to the way businesses are conducted. Mobility has become one of the main priorities for users and this has impacted on cellular networks and telecommunication operators (CNTOs). However, entrants into the cellular industry have been confounded primarily by inexistent or weak Business Models (BMs). Designing a BM for a CNTO is complex and requires multiple actors to balance different and often conflicting design requirements. Nevertheless, most research about CNTOs has been technically oriented and has mainly addressed the technological and engineering issues related to their infrastructure. Less attention has been given to the business model of CNTOs. Hence, there is a need to enhance our ability to determine what constitutes the optimal and most viable business model to meet the various strategic objectives and goals for these CNTOs. In this paper an overview of research into the cellular business model and the main issues to be resolved is provided. In particular, the authors propose guidelines as a basis on which to develop a more comprehensive definition which may lead to a consensus. Moreover, a generic model (V4 Model) is proposed for the BM of these companies based on value proposition, value architecture, value network and value finance

Development of iSpeak: A voice activated Relationship Management System

A constant source of frustration for subscribers of mobile telephony in Nigeria is the quality of customer care service. The ubiquitous IVR systems deployed by service providers often ends in long and winding texting of digits that terminate in calls to agents with poor CRM attitudes. Automation of most of the functions of the human agent goes a long way in mitigating this problem. This paper describes iSpeak – a system designed to reduce the human–to–human (H2H) interaction in the complaint-lodging and solution provision process to a minimal level where it is not possible to eradicate it totally by a replacement with human–to–system (H2S) interactivity. iSpeak has an inherent capacity for improving the efficiency and drastically cutting CRM cost of corporate organizations. This comes with the attendant advantage of improved business-customer relationship. Keywords – Automatic Speech Recognition, Customer Care Service, Speech-control, Customer Voice Model, Voice Print, Voice Recognition

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history