Credit Ranking of Bank Customers (An Integrated Model of RFM, FAHP and K-means)

In this paper, with the aim to rank customers in terms of credit, three patterns namely Hsieh (RFM), FAHP, and K-means were integrated. The main effective factors on ranking customers including transactions, repayment and RFM (Recency, Frequency and Monetary) variables were defined. For classifying the legal customers of Export Development Bank of Iran in terms of credit, 5 variables were extracted from the bank’s database and normalized accordingly. The weight of each variable was calculated through interviewing bank experts using FAHP. Using the values of the variables and K-means algorithm, the optimal clusters of customers were determined. Finally, bank customers were ranked in 5 credit clusters and the value of each cluster was estimated. According to the findings, recency, repayment behavior, transaction, frequency, and monetary variables had maximum effects on customers’ ranks, respectively. Therefore, 54% of the customers fell in the third cluster (with cluster value of 0.95) and the fifth cluster (with cluster value of 0.76) composed of good and very good customers. Credit risk of the two clusters (especially the third one) was at least. 32% of the customers positioned in the second cluster (with cluster value of 0.59) including the average customers in terms of credit. 14% of the customers fell in the fourth and first clusters with cluster values of 0.42 and 0.26 including highest risky customers

Risk prediction of product-harm events using rough sets and multiple classifier fusion:an experimental study of listed companies in China

With the increasing of frequency and destructiveness of product-harm events, study on enterprise crisis management becomes essentially important, but little literature thoroughly explores the risk prediction method of product-harm event. In this study, an initial index system for risk prediction was built based on the analysis of the key drivers of the product-harm event's evolution; ultimately, nine risk-forecasting indexes were obtained using rough set attribute reduction. With the four indexes of cumulative abnormal returns as the input, fuzzy clustering was used to classify the risk level of a product-harm event into four grades. In order to control the uncertainty and instability of single classifiers in risk prediction, multiple classifier fusion was introduced and combined with self-organising data mining (SODM). Further, an SODM-based multiple classifier fusion (SB-MCF) model was presented for the risk prediction related to a product-harm event. The experimental results based on 165 Chinese listed companies indicated that the SB-MCF model improved the average predictive accuracy and reduced variation degree simultaneously. The statistical analysis demonstrated that the SB-MCF model significantly outperformed six widely used single classification models (e.g. neural networks, support vector machine, and case-based reasoning) and other six commonly used multiple classifier fusion methods (e.g. majority voting, Bayesian method, and genetic algorithm)

ISBIS 2016: Meeting on Statistics in Business and Industry

This Book includes the abstracts of the talks presented at the 2016 International Symposium on Business and Industrial Statistics, held at Barcelona, June 8-10, 2016, hosted at the Universitat Politècnica de Catalunya - Barcelona TECH, by the Department of Statistics and Operations Research. The location of the meeting was at ETSEIB Building (Escola Tecnica Superior d'Enginyeria Industrial) at Avda Diagonal 647. The meeting organizers celebrated the continued success of ISBIS and ENBIS society, and the meeting draw together the international community of statisticians, both academics and industry professionals, who share the goal of making statistics the foundation for decision making in business and related applications. The Scientific Program Committee was constituted by: David Banks, Duke University Amílcar Oliveira, DCeT - Universidade Aberta and CEAUL Teresa A. Oliveira, DCeT - Universidade Aberta and CEAUL Nalini Ravishankar, University of Connecticut Xavier Tort Martorell, Universitat Politécnica de Catalunya, Barcelona TECH Martina Vandebroek, KU Leuven Vincenzo Esposito Vinzi, ESSEC Business Schoo

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Decision Maps for Distributed Scenario-Based Multi-Criteria Decision Support

This thesis presents the Decision Map approach to support decision-makers facing complex uncertain problems that defy standardised solutions. First, scenarios are generated in a distributed manner: the reasoning processes can be adapted to the problem at hand whilst respecting constraints in time and availability of experts. Second, by integrating scenarios and MCDA, this approach facilitates robust decision-making respecting multiple criteria in a transparent well-structured manner

Hydrothermal processing of biogenic residues in Germany: A technology assessment considering development paths by 2030

The mining, processing, and use of finite natural resources is associated with significant interventions in the natural environment. Thus, these and other negative consequences make it necessary to reduce resource consumption. An important field of action is the more efficient use of biogenic residues as secondary raw materials. However, high water containing biomasses are still a problem since they need an energy- and cost-intensive pre-treatment for many conversion processes, which can make their use uneconomical. Hydrothermal processes (HTP) seem to be promising, since they require an aqueous environment for optimal processing anyway. Although technological progress within the industry is recognisable, however, to date HTP have not been established in industrial continuous operation in Germany. The core of this work is identifying reasons for this sluggish development and deriving appropriate recommendations for action. Based on the hypothesis that HTP can contribute to the efficient utilisation of biogenic residues in the future, potentials and obstacles for the development of HTP in Germany are identified using a literature review, expert survey, expert workshop, and SWOT analysis. To estimate the future potential of HTP in a systematic and structured way, a multi-criteria technology assessment approach is developed based on the results. To this end, assessment criteria for HTP are derived, weighted by expert judgment, and integrated into a transparent and structured procedure. In addition, mainly based on a Delphi-survey key factors of HTP development by 2030 in Germany are identified and three development alternatives for HTP in Germany by 2030 are derived. Using a system analysis and a comparative multi-criteria analysis at plant level, these scenarios are analysed for their possible future impact. Based on this methodology, the work shows that the production costs for the end products, the energy efficiency of the process, and the proportion of recycled phosphorus are of high relevance to the techno-economic success of HTP compared to reference systems, and they are therefore of high importance for its future development on the plant level. In addition, further key factors for the future development of HTP in Germany on the system level are found to be mainly in the political-legal (e.g. legal waste status of products from HTP) and techno-economic (e.g. cost-effective process water treatment) areas. According to this, important fields of action are the identification and use of cost reduction potentials (e.g. heat waste use), the development of system integrated decentralised plant concepts with integrated nutrient recycling (e.g. phosphorus), and the development of cost-effective ways to treat process water. System integration, cost-effective process water treatment, and nutrient recycling are all closely linked to production costs, investment costs, and potential revenues, and can contribute to improved process economics. For these areas, there is promising future potential to achieve higher competitiveness with reference technologies that are currently more economical.:Bibliographic description Curriculum Vitae Selbstständigkeitserklärung Danksagung List of Publications Contribution to the Publications Contents List of Acronyms List of Tables List of Figures Part I Introductory Chapters 1 Introduction and Background Hydrothermal processes: Introduction and status quo State of the art in the research field and knowledge gaps Objective and research framework Expected value added of this work 2 Materials and methods Derivation of HTP evaluation metrics and technology assessment tool Derivation of key HTP development factors and scenarios Performing the system-level scenario analysis Plant-level scenario analysis and test application of the assessment tool Derivation of core recommendations 3 Results and discussion Key development factors for HTP in Germany and scenarios System-level scenario analysis Test application of the assessment tool on plant level scenarios Recommendations Discussion 4 Conclusion and outlook Future research Further fields for the application of the developed methods 5 References Part II Appended Articles Paper I Paper II Paper III Paper IV Paper V Paper VIDer Abbau, die Verarbeitung und die Nutzung endlicher natürlicher Ressourcen sind mit erheblichen Eingriffen in die natürliche Umwelt verbunden. Diese und andere negative Folgen machen es daher erforderlich, den Ressourcenverbrauch zu senken. Ein wichtiges Handlungsfeld ist die effizientere Nutzung biogener Reststoffe als Sekundärrohstoffe. Stark wasserhaltige Biomassen sind jedoch ein Problem, da sie für viele Umwandlungsprozesse eine energie- und kostenintensive Vorbehandlung benötigen, was ihre Verwendung unwirtschaftlich machen kann. Hydrothermale Prozesse (HTP) scheinen für diese Reststoffe allerdings vielversprechend zu sein, da sie ohnehin eine wässrige Umgebung für eine optimale Verarbeitung benötigen. Obwohl der technologische Fortschritt innerhalb der Branche erkennbar ist, wurde HTP in Deutschland bisher nicht im industriellen Dauerbetrieb etabliert. Der Kern dieser Arbeit besteht darin, Gründe für diese schleppende Entwicklung zu ermitteln und geeignete Handlungsempfehlungen abzuleiten. Basierend auf der Hypothese, dass HTP in Zukunft zur effizienten Nutzung biogener Reststoffe beitragen können, werden Potenziale und Hindernisse für deren Entwicklung in Deutschland anhand einer Literaturrecherche, einer Expertenumfrage, eines Expertenworkshops und einer SWOT-Analyse ermittelt. Um das zukünftige Potenzial von HTP systematisch und strukturiert abzuschätzen, wird basierend auf den Ergebnissen ein multi-kriterieller Technologiebewertungsansatz entwickelt. Zu diesem Zweck werden Bewertungskriterien für HTP abgeleitet, nach Expertenmeinung gewichtet und in ein transparentes und strukturiertes Verfahren integriert. Darüber hinaus werden hauptsächlich auf der Grundlage einer Delphi-Umfrage Schlüsselfaktoren für die HTP-Entwicklung bis 2030 in Deutschland identifiziert und drei Entwicklungsalternativen für HTP in Deutschland bis 2030 abgeleitet. Mithilfe einer Systemanalyse und einer vergleichenden multi-kriteriellen Analyse auf Anlagenebene werden diese Szenarien auf ihre möglichen zukünftigen Auswirkungen hin analysiert. Basierend auf dieser Methodik zeigen sich als Ergebnisse, dass die Produktionskosten für die Endprodukte, die Energieeffizienz der Prozesse und der Anteil an recyceltem Phosphor für den techno-ökonomischen Erfolg von HTP im Vergleich zu Referenzsystemen von hoher Relevanz und daher auch von hoher Bedeutung für die zukünftige Entwicklung auf Anlagenebene sind. Darüber hinaus liegen weitere Schlüsselfaktoren für die künftige Entwicklung von HTP in Deutschland auf Systemebene hauptsächlich im politisch-rechtlichen (z. B. legalen Abfallstatus von Produkten aus HTP) und techno-ökonomischen (z. B. kostengünstige Prozesswasseraufbereitung)) Bereichen. Wichtige Handlungsfelder sind demnach die Ermittlung und Nutzung von Kostensenkungspotentialen (zB Abwärmenutzung), die Entwicklung systemintegrierter dezentraler Anlagenkonzepte mit integriertem Nährstoffrecycling (z.B. Phosphor) und die Entwicklung kostengünstiger Wege zur Prozesswasserbehandlung. Systemintegration, kostengünstige Prozesswasseraufbereitung und Nährstoffrecycling hängen eng mit Produktionskosten, Investitionskosten und potenziellen Einnahmen zusammen und können zu einer verbesserten Wirtschaftlichkeit der Prozesse beitragen. Für diese Bereiche besteht ein vielversprechendes Zukunftspotenzial für eine höhere Wettbewerbsfähigkeit zu Referenztechnologien, die derzeit noch wirtschaftlicher sind.:Bibliographic description Curriculum Vitae Selbstständigkeitserklärung Danksagung List of Publications Contribution to the Publications Contents List of Acronyms List of Tables List of Figures Part I Introductory Chapters 1 Introduction and Background Hydrothermal processes: Introduction and status quo State of the art in the research field and knowledge gaps Objective and research framework Expected value added of this work 2 Materials and methods Derivation of HTP evaluation metrics and technology assessment tool Derivation of key HTP development factors and scenarios Performing the system-level scenario analysis Plant-level scenario analysis and test application of the assessment tool Derivation of core recommendations 3 Results and discussion Key development factors for HTP in Germany and scenarios System-level scenario analysis Test application of the assessment tool on plant level scenarios Recommendations Discussion 4 Conclusion and outlook Future research Further fields for the application of the developed methods 5 References Part II Appended Articles Paper I Paper II Paper III Paper IV Paper V Paper V

Video advertisement mining for predicting revenue using random forest

Shaken by the threat of financial crisis in 2008, industries began to work on the topic of predictive analytics to efficiently control inventory levels and minimize revenue risks. In this third-generation age of web-connected data, organizations emphasized the importance of data science and leveraged the data mining techniques for gaining a competitive edge. Consider the features of Web 3.0, where semantic-oriented interaction between humans and computers can offer a tailored service or product to meet consumers\u27 needs by means of learning their preferences. In this study, we concentrate on the area of marketing science to demonstrate the correlation between TV commercial advertisements and sales achievement. Through different data mining and machine-learning methods, this research will come up with one concrete and complete predictive framework to clarify the effects of word of mouth by using open data sources from YouTube. The uniqueness of this predictive model is that we adopt the sentiment analysis as one of our predictors. This research offers a preliminary study on unstructured marketing data for further business use