Using hybrid technique: the integration of data analytics and queuing theory for average service time estimation at Immigration Service, Suvarnabhumi Airport

In the past few years, Thai tourism industry has become one of the big markets in the world that makes the number of air passenger has growth rapidly.The survey shows that 15,883,928 passengers arrived at Suvarnabhumi international airport, Thailand in 2015 which increase around 11% every year.Due to this reason, the airport needs to seek for effective strategies to operate an immigration service in order to avoid long waiting time.The effective immigration operation actually can gain passenger satisfaction. In addition, the fast immigration process provides the significant benefit for businesses in the airport because short immigration waiting time would be able to increase the purchase amount in shopping area.This paper aims to propose the hybrid method, the intregration of data analytics and queuing theory, for average service time estimation at the immigration unit, Suvarnabhumi airport. From the experimental study, the proposed technique can estimate the average service time, server utilization and average number of passengers in a queue based on the statistic of arrival passengers. The result shows that the number of opened counter and month are the factors to provide different results

Churn prediction models tested and evaluated in the Dutch indemnity industry

Due to global developments customer churn is getting a growing concern to the insurance industry. Technological improvements like the internet makes it much easier for customer to compare their policies, obtain new offers or even churn from one provider to another. The insurance industry therefore has become a heavily competitive market in which insurance companies have to compete to protect and expand their customer base in order to maintain or expand their market position. Thus, retaining customers is becoming more and more important and therefore finding customers who are most likely to leave is a central aspect. Many different techniques are available to identify customers who are most likely to leave, however which technique can be used best is often not clear. Research clarifies that the characteristics of the industry and/or dataset which is used are mostly assessing related to performance. In advance it is impossible to determine the best suited technique to use if previous research in which performance was tested has not been published. This study presents a data mining methodology in which the four most used prediction techniques in literature are tested and evaluated using a real life voluminous insurance company dataset to determine which technique performs best. Using the same dataset makes results comparable and clears out which technique performs best based on the insurance data domain characteristics

Um modelo para previsão de churn na área do retalho

Dissertação de mestrado em Engenharia de InformáticaO ambiente de grande competitividade característico do sector do retalho e crescente dificuldade na captação de novos clientes leva as empresas a apostar na implementação de estratégias adequadas para promover a satisfação dos clientes adquiridos para motivar a sua lealdade. É neste contexto que se começa a reconhecer a importância de combater o fenómeno de churn, ou seja, a perda de clientes. É necessário identificar os clientes que estão em risco de churn e, para isso, é necessário criar um método que o permita fazer com antecedência para que possam recair sobre eles as campanhas de retenção proactivas. Quanto mais eficaz for o método a identificar os clientes em riscos, maior será o retorno da aplicação da campanha. Muitos trabalhos têm sido desenvolvidos na área de previsão de churn nos mais diversos sectores. Contudo, na área do retalho a pesquisa têm sido muito limitada. Assim, com este trabalho de dissertação pretendeu-se estudar o fenómeno da perda de clientes com o objectivo de definir e implementar um modelo de churning para o sector do retalho recorrendo a técnicas de mineração de dados. Pretendeu-se fazer um levantamento das principais questões envolvidas na previsão de churn no retalho, na construção do conjunto de dados (assinaturas dos clientes) e na aplicação de técnicas de mineração de dados no processo de previsão. Nesse sentido, foram construídos alguns modelos para fazer a previsão de casos de churn baseados em cinco das técnicas de classificação mais utilizadas em trabalhos de previsão de churn: Árvores de Decisão, Regressão Logística, Redes Neuronais, Random Forests e SVM. A avaliação e comparação da performance dos modelos elaborados foi feita de acordo com várias medidas como accuracy, precision, sensitivity, specificity, f-measure e AUC e, para além disso, foi testado o impacto, na precisão do modelo, da alteração da densidade de eventos de churn no conjunto de treino.The great competitive environment characteristic of the retail sector and increasing difficulty in attracting new customers leads firms to invest in the implementation of appropriate strategies to promote customer satisfaction to motivate their loyalty. It is in this context that we begin to recognize the importance of combating the phenomenon of churn, i.e., the loss of clients. It is necessary to identify customers who are at risk of churn and, therefore, it is necessary to create a method that allows to do it in advance so that they can be covered by the proactive retention campaigns. The more effective the method to identify customers at risk, the higher the return of applying the campaign. Many studies have been developed in the area of churn prediction in various sectors. However, in the area of retail the research has been very limited. So with this dissertation work was intended to study the phenomenon of loss of customers to define and implement a model of churning to the retail sector using data mining techniques. The intention was to make a survey of the main issues involved in the prediction of churn in retail, construction of the dataset (customer signatures) and applying data mining techniques in the forecasting process. Accordingly, some models were constructed to forecast cases of churn based on five of the most commonly used classification techniques in churn prediction: Decision Trees, Logistic Regression, Neural Networks, Random Forests and SVM. The evaluation and comparison of the performance of models developed has been made according to several measures as accuracy, precision, sensitivity, specificity, f-measure and AUC and, furthermore, has been tested the impact of the change in the density of churn events in the training set

Technology-driven industry evolution in the telecom sector: The comparative case of Ecuador

The purpose of this Thesis is to analyze the current situation of the telecom industry in Ecuador and its tendencies as part of the Telecom, Media and Technology TMT industry. The analysis elaborates about the ongoing effects at the industry and business levels of the widespread of mainstream products and services in the TMT market in the case of Ecuador, benchmarking it with the global context. In this sense, the case study is developed by addressing the following question: How the widespread of mainstream products and services in the TMT market are and might continue shaping the development of the telecom industry in Ecuador in the next decade and how does it compare to the global environment? About the research question, in this thesis it is evidenced that the development of the telecom industry in Ecuador has been boosted by the widespread of mainstream products and services in the TMT market including broadband fixed and mobile internet, smartphones, social networks, HDTV, e-commerce and OTT content. Furthermore, it is argued that the deployment of next generation networks represents a technological discontinuity that cannot be overlooked by firms, and become determinant for the future performance of firms. In order to achieve its goal, the Thesis has been structured as follows: A brief review of the telecom industry evolution and its present and future challenges are provided in the first chapter, as well as the specificities of the development in Ecuador. In the second chapter, the predominant approaches about organization development and change are discussed openly. Further on, a compressed review of the telecom ecosystem as part of the TMT industry is provided in chapter three in order to identify the forces driving the industry. Chapter four presents the methodology used in this study and then the case study is developed in chapter five, in which I attempt to depict the current situation of the telecom industry in Ecuador and its tendencies as part of the TMT industry, while reflecting on the theoretical framework presented in the literature review section. Finally a general discussion of the findings and conclusion are provided