| Preface |
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| Acknowledgment |
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| Section 1 Consumer Analytics: Fuzzy Applications |
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Chapter 1 A New Perspective on RFM Analysis |
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1 | (20) |
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The aim of this chapter is proposing a novel integrated Fuzzy Group Multiple Attribute Decision Making (FGMADM) and Fuzzy C-Means Clustering (FCM) as a DM tool for segmentation of customers (retailers), based on an updated RFM model. |
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For this purpose, the most important criteria to evaluate retailers from the in depth literature survey and experts' opinion are added to the traditional RFM model. |
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In addition, in order to make the model more efficient, FGMADM approach, in this paper, Fuzzy Group Step-wise Weight Assessment Ratio Analysis (FGSWARA) is used to weight KPIs. |
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Then, FCM is applied to segment customers, based on their purchase behavior (RFM scores). |
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A case study in one of the most famous Fast Moving Consumer Goods (FMCG) companies in Iran illustrated the applicability of the proposed model. |
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Chapter 2 A Novel Approach to Segmentation Using Customer Locations Data and Intelligent Techniques |
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21 | (19) |
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Customer segmentation has been one of hottest topics of marketing efforts. |
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The traditional sources of data used for segmentation are demographics, monetary value of transactions, types of product/service selected. |
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Today, data gathered by location based services can also be used for customer segmentation. |
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In this chapter a real world case study is summarized and the initial segmentation results are presented. |
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As the application, data gathered from beacons sited in 4000 locations and Fuzzy c-means clustering algorithm are used. |
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The steps of the application are as follows: |
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1 Categorization of the shops |
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2 Summarization of the location data |
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3 Applying fuzzy clustering technique |
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4 Analyzing the results and profiling |
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Results show that customers' location data can provide a new perspective to customer segmentation. |
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Chapter 3 Fuzzy Clustering: An Analysis of Service Quality in the Mobile Phone Industry |
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40 | (22) |
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This chapter presents a study of the development of the clustering methodology to data analysis, with particular attention to the analysis from a crisp environment to a fuzzy environment. |
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An applied problem concerning service quality (using SERVQUAL) of mobile phone users, and subsequent loyalty and satisfaction forms the data set to demonstrate the clustering issue. |
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Following details on both the crisp k-means and fuzzy c-means clustering techniques, comparable results from their analysis are shown, on a subset of data, to enable both graphical and statistical elucidation. |
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Fuzzy c-means is then employed on the full SERVQUAL dimensions, and the established results interpreted before tested on external variables, namely the level of loyalty and satisfaction across the different clusters established. |
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Chapter 4 An Analysis of the Interactions among the Enablers of Information Communication Technology in Humanitarian Supply Chain Management: A Fuzzy-Based Relationship Modelling Approach |
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62 | (13) |
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The rise in the occurrence of disasters has hampered the development of many countries. |
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Practitioners and academicians are making continuous demands to enhance the utilization of information communication technologies (ICTs) in humanitarian supply chain management (HSCM) in order to continue or enhance the pace of economic growth and development of countries, as well as to reduce the impact of disaster on society. |
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Identifying and analysing key decision variables improving the utilization of ICT in HSCM is essential in trying to improve overall performance. |
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Therefore, to assist the organizations involved in HSCM, this study explores eleven enablers to enhancing the utilization of ICTs, with a focus on the mutual relationship among them using an integrated interpretive structural modeling (ISM) and fuzzy cross-impact matrix multiplication applied to classification (F-MICMAC) analysis. |
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This study seeks to advance the understanding on enablers of ICTs in HSCM and to classify them, on the basis of driving and dependence power. |
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| Section 2 Computational Intelligence: Business Analytics |
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Chapter 5 Auto Associative Extreme Learning Machine Based Hybrids for Data Imputation |
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75 | (25) |
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This chapter presents three novel hybrid techniques for data imputation viz.. |
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1 Auto-associative Extreme Learning Machine (AAELM) with Principal Component Analysis (PCA) (PCA-AAELM). |
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2 Gray system theory (GST) + AAELM with PCA (Gray+PCA-AAELM). |
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3 AAELM with Evolving Clustering Method (ECM) (ECM-AAELM). |
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Our prime concern is to remove the randomness in AAELM caused by the random weights with the help of ECM and PCA. |
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This chapter also proposes local learning by invoking ECM as a preprocessor for AAELM. |
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The proposed methods are tested on several regression, classification and bank datasets using 10 fold cross validation. |
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The results in terms of Mean Absolute Percentage Error (MAPE,) are compared with that of K-Means+Multilayer perceptron (MLP) imputation, K-Medoids+MLP, K-Means+GRNN, K-Medoids+GRNN, PSO_Covariance imputation and ECM-Imputation. |
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It is concluded that the proposed methods achieved better imputation in most of the datasets as evidenced by the Wilcoxon signed rank test. |
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Chapter 6 Multi-Criteria Decision Making in Marketing by Using Fuzzy Rough Set |
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100 | (19) |
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Most of the marketing problems are complex and unstructured due to the business dynamics and considerable uncertainty involved in the operating environments. |
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Hence decision making in marketing involves evaluation of several parameters and thus multi criteria decision makings are a good choice in most of the decision-making tasks like supplier selection; market places selection; target marketing; etc. |
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This chapter begins with a brief introduction of the theory of rough set which is an intelligent technique for handling uncertainty aspect in the data. |
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However, the notions of fuzzy rough set and intuitionistic fuzzy rough (IFR) sets are defined, and its properties are studied. |
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Thereafter rough set on two universal sets has been studied. |
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In addition, intuitionistic fuzzy rough set on two universal sets has been extensively studied. |
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Furthermore, this chapter shows that intuitionistic fuzzy rough set can be successfully practiced in decision making problems. |
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Chapter 7 Fuzzy Multi-Objective Association Rule Mining Using Evolutionary Computation |
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119 | (30) |
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In this chapter, we model association rule mining as a Fuzzy multi-objective global optimization problem by considering several measures of strength such as support, confidence, coverage, comprehensibility, leverage, interestingness, lift and conviction by utilizing various fuzzy aggregator operators. |
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In this, pdel, each measure has its own level of significance. |
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Three fuzzy multi-objective association rule mining techniques viz., Fuzzy Multi-objective Binary Particle Swarm Optimization based association rule miner (FMO-BPSO), a hybridized Fuzzy Multi-objective Binary Firefly Optimization and Threshold Accepting based association rule miner (FMO-BFFOTA), hybridized Fuzzy Multi-objective Binary Particle Swarm Optimization and Threshold Accepting based association rule miner (FMO-BPSOTA) have been proposed. |
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These three algorithms have been tested on various datasets such as book, food, bank, grocery, click stream and bakery datasets along with three fuzzy aggregate operators. |
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From these experiments, we can conclude that Fuzzy-And outperforms all the other operators. |
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Chapter 8 Improved Seating Plans for Movie Theatre to Improve Revenue: An Integrated Best Worst Method with EMSR-B |
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149 | (11) |
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Bollywood is not only one of the biggest film producers in India but also one of the largest centers of film production in the world. |
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Seat occupancy rate and pricing of each seat are important parameters that determines the revenue of a cinema business. |
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The objective of the chapter is to enable theater managers to determine the prices at the time of booking according to the occupancy rate so that the revenue is improved based on preferred demand for the respective seats. |
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A multi criteria analysis is applied with seat occupancy rate as dependent variable and other factors as independent variables like Show time, Poster Size, Day of week and Timing of Release. |
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Further, a predictive analysis can be carried out to determine the occupancy rate for the upcoming movies. |
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Based on the occupancy rate, the managers at theater can adopt variable pricing concept to improve the revenue. |
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This work shows an integrated method to develop a seating plan based on occupancy rate to improve the revenue using EMSR-b heuristic with an illustrated example for a theater. |
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| Section 3 Consumer Analytics: Multi-Criteria (MCDM) Applications and Sentiment Analysis |
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Chapter 9 Applications of the Stochastic Multicriteria Acceptability Analysis Method for Consumer Preference Study |
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160 | (25) |
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Introducing a new product to the market is a complex, costly and time-consuming process which requires research on consumer preferences. |
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On the basis of information on the characteristics of the new product and its competitors, as well as on the competitors and their market shares, the company has to estimate future market shares and to determine the profile of potential consumers inclined to purchase the new product. |
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The purpose of our paper is to present a method of consumer preference research when introducing a new product, using a multiple criteria method called Stochastic Multicriteria Acceptability Analysis (SMAA). |
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To apply this method, no information requiring tedious research is needed. |
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SMAA allows to obtain essential information on the potential market power of the new product already at an early stage of its preparation. |
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Furthermore, the flexibility of the SMAA method allows to easily expand the scope of the analysis by including additional information and various techniques of the modeling of the consumer selection process. |
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Chapter 10 Modeling Consumer Opinion Using RIDIT and Grey Relational Analysis |
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185 | (17) |
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In order to understand consumers, researchers are forced to gather primary data on Likert scale. |
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Such data is usually considered as ordinal or at best interval scaled data. |
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One key requirement in research is to identify components which have high individual contribution to understanding the research problem. |
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Hence the concept of ranking of the components comes under consideration. |
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Most of the ranking techniques are based on simplistic mean ranks or overtly complicated methods. |
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In this chapter the authors highlight two techniques - Grey Relational Analysis (GRA) and RIDIT - for the purpose. |
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In this chapter the authors explain the techniques of the two methods and then try to show the simplicity and efficiency of GRA and RIDIT algorithms in analyzing a commonly available dataset. |
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The outcome of the GRA and RIDIT analysis is also compared with the commonly used techniques and the authors would examine if GRA and RIDIT does a better job at ranking data than the commonly used techniques. |
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Chapter 11 Sentiment Analysis as a Tool to Understand the Cultural Relationship between Consumer and Brand |
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202 | (14) |
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One of the most relevant issues that companies, offices and marketing experts, sociologists and scholars must address studying a new brand or product launch is without any doubt the impact - in terms of feedback - on the consumer sentiment. |
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The study of users' opinions on a specific product or brand has changed with the advent of Web 2.0, which has overcome the old surveys model leading consumers in a too complex and not genuine area, reaching more sophisticated research or even better tracking their opinions directly "on the field", i.e. in the community where this exchange of views and information happens naturally and not artificially. |
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The analysis of consumers' opinions on social media provides enormous opportunities for the public and the private spheres. |
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Concerning the last on the reputation of a certain product/brand or firm is strongly influenced by the voices and negative opinions published and shared by users on social networks. |
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Indeed, companies need to adapt their behaviour monitoring public opinion. |
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Chapter 12 Improving Customer Experience Using Sentiment Analysis in E-Commerce |
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216 | (10) |
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In today's world, millions of online users post their opinions on product features, services, quality, benefits and other values of the products. |
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These opinions or sentiment data generated via different communication mediums often include vital data points that can be fruitful for businesses in understanding customer experiences, products quality and services. |
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The E-commerce companies considered social media platform for new product launch, promotion of products and features or establishing a successful business to customer relationship which produces great results. |
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Analytics on this Social media data helps in identifying the customers in the right demographic, psychographic and lifestyle group. |
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This chapter identifying important characteristics of customer reviews which help businesses houses to improve their marketing strategies. |
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| Section 4 Marketing Analytics: Digital Market Place |
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Chapter 13 Adoption of Online Marketing for Service SMEs with Multi-Criteria Decision-Making Approach |
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226 | (18) |
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Rosalin Merry Berdin Alarde |
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Dennis Anthony Kilongkilong |
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This chapter attempts to fill in the gap of evaluating the viability of adopting online marketing for small and medium enterprises (SMEs) in service industries. |
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As SMEs are generally characterized by shortage of resources, the use of online marketing strategies is apparently difficult. |
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However, the current landscape of competition among SMEs in a global market economy prompts the necessity of adopting online marketing. |
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With these, the decision-making process of SMEs in this area becomes complex and the decisions must integrate complex and interrelating criteria and constructs in order to provide a more holistic solution. |
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Thus, this work adopts a multi-criteria decision-making (MCDM) method particularly the analytic network process (ANP) in order to evaluate the practicability of using online marketing for service SMEs. |
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It becomes highly relevant as it provides significant insights to decision-makers in SMEs regarding the use of online marketing strategy. |
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The contribution of this chapter lies in the application of MCDM in evaluating viability of online marketing in service SMEs. |
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Chapter 14 E-Retailing from Past to Future: Definitions, Analysis, Problems, and Perspectives |
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244 | (14) |
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In this chapter, first, the definition, the advantages and disadvantages of e-retailing are given and the related literature about e-retailing is briefly explained in order to give a background to unfamiliar readers. |
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Then, the qualitative and quantitative criteria which affect the e-retailer selection are determined and some e-retailers are evaluated by using a multi-phase, integrated Multi Criteria Decision Making (MCDM) approach. |
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In first phase of proposed MCDM approach, the weight of each criterion is determined. |
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In second phase, a pre-evaluation is made and some of the e-retailers are eliminated. |
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In last phase, the remaining retailers are evaluated and the best one is determined. |
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Finally, the study is concluded by discussions, inferences and recommendations for future work. |
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Chapter 15 Fuzzy Time Series: An Application in E-Commerce |
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258 | (33) |
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In this chapter, we are planning to make a comparison between conventional Time Series Models and Fuzzy Time Series Models by an application in an e-commerce company. |
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Future sales of furniture will be predicted. |
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The performance of different models and forecasting periods are going to be analyzed to discuss advantages and disadvantages of each method. |
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MAE is chosen as performance indicators of each model and forecasting period combination. |
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As a conclusion to this chapter, generic strategies for prediction in an e-commerce company will be formulated in consideration of these indicators. |
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Chapter 16 Understand the Frequency of Application Usage by Smartphone Users: Door Is Open, but Closes Quickly |
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291 | (14) |
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Smartphone users download the apps after the enormous popularity in this mobile world and then eventually delete those apps. |
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There are various factors like frequency, relevance and space it consumes in the phone, which decide a user's preference for an app. |
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All the app provider companies are trying hard to fit into right place, so that they can increase the engagement with the users. |
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Companies are upgrading their technology to make an app convenient and relevant based on user's requirement. |
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This study is trying to understand the frequency of application usage and the importance of various factors like time to complete transaction, relevance, space it consumes, features, User Index, and ease of use for a user which leads to purchase intention. |
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The study has found that UX/UI is the most important factor followed by other factors. |
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The output of the study has the practical implication for online retailer. |
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| Section 5 Advanced Modelling Applications: Business Analytics |
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Chapter 17 Car Safety: A Statistical Analysis for Marketing Management |
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305 | (27) |
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Car safety is an essential feature of marketing strategies for automobile companies. |
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In this work, a statistical analysis on crash tests is conducted based on data available from European New Car Assessment Programme (Euro NCAP). |
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The research work developed in this chapter presents a statistical analysis of the information produced by Euro NCAP, using the SPSS and MATLAB software, and seeks to answer the following research questions: - are there statistically significant differences on adult occupant safety in the six years under study? - are there statistically significant differences among the best-selling car classes regarding safety in frontal collisions? - are electric and hybrid automobiles less secure than their traditional counterparts with respect to frontal collisions? |
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Chapter 18 Banking Credit Scoring Assessment Using Predictive K-Nearest Neighbour (PKNN) Classifier |
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332 | |
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Credit scoring models is a scientific methodology adopted by credit providers to assess the credit worthiness of applicants. |
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The primary objective of such models has been to predict the potentiality of the loan applicant. |
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A proper evaluation of the credit can help the service provider to determine whether to grant or to reject credit. |
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Therefore, the objective of the study is to predict banking credit scoring assessment using Predictive K-Nearest Neighbour (PKNN) classifier. |
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For the purpose of analysis two different credit approval datasets: Australian credit and German credit have been used. |
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The results from the study show that the proposed model used for classification works better on credit dataset. |
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Here, the study firstly attempted to find the optimal 'IC value of the neighbourhood so that the classifier is tuned to forecast the credit worthiness and secondly, validated our proposed model on two credit approval datasets by checking the performance of the proposed models on the basis of classification accuracy. |
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Chapter 19 Prediction of the Quality of Fresh Water in a Basin |
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151 | (217) |
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Derivatives play an important role in social and economic studies. |
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They describe the behavior of conditional expectations. |
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Once a phenomena is characterized by parametric specifications, the conditional expectation m(x) may be modeled by a regression function. |
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Then, derivatives may be computed by fitting the regression function. |
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In applications, parametric estimators are commonly used, because of the un-knowledge of other more effective methods. |
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The validity of a regression fitting approach depends on the knowledge of certain aspects related with the true functional form. |
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In this paper, we develop a study on the usage of soft computing methods for providing an alternative to the use of non-parametric regression. |
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We develop our modeling including neural networks and rough sets approaches. |
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The studied problem is the eutrophication due to the growth of the population of algae. |
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Real life data is provided by a study on a fresh water basin. |
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They are used for developing a comparison of different approaches. |
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A methodology is recommended for implementing a monitoring system of the water quality. |
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Chapter 20 Operating Commodities Market by Automated Traders |
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368 | (13) |
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This is an introductory work to the field of automatizing futures markets, related to commodities, so far operated by human traders. |
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First, we build a mathematical framework for a futures market with many producers and consumers represented by automated traders in the market platform. |
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Then we suggest an automatic trading strategy for the automatons. |
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This strategy takes into account the forecasts of supply and demand streams as well as the evolution of nominal price. |
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Later, we recall a set of analytical criteria used to measure the performance of a trading strategy. |
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Next, we illustrate our approach by showing a price pattern generated by the automatic strategy and calculate its performances. |
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Finally, we exhibit a heuristic based on simulation allowing to compute a quasi-optimal parameters matrix for this automatic trading system. |
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| Compilation of References |
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381 | (37) |
| About the Contributors |
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| Index |
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