Case: AMERICAN CHEMICAL CORPORATION 1. Executive Summary Dixon‚ an American specialty chemical producer‚ wants to buy Collinsville plant from American Chemical Corporation‚ another typical chemical company in 1979. Dixon wants to diversify its product line buy acquiring the aforesaid plant‚ which produces sodium-chlorate to supply to paper producers in Southeastern part of the US. This plant initially cost 12 mln. USD and additional 2‚25 mln. USD needed to buy laminate technology to increase efficiency
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com/locate/eswa Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty Seyed Mohammad Seyed Hosseini *‚ Anahita Maleki‚ Mohammad Reza Gholamian Industrial Engineering Department‚ Iran University of Science and Technology‚ Tehran‚ Iran a r t i c l e i n f o a b s t r a c t Data mining (DM) methodology has a tremendous contribution for researchers to extract the hidden knowledge and information which have been inherited in the data used by researchers.
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Executive Summary American Chemical Corporation’s Collinsville plant in Alabama is being sought by Dixon a speciality chemicals company. This plant mainly specialises in Sodium Chlorate production and fits well with Dixon’s strategy of supplying chemicals to paper and pulp industry. It would also complement Dixon’s existing product line. The plant costs $12million in investment and requires up to$ 2.25 million for upgrading to new technology. An in-depth investigation and analysis is conducted
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White Paper CRM vs. Loyalty Programs: Best Friends or Arch Rivals? CRM vs. Loyalty Best Friends or Arch Rivals? A sk business owners what keeps them up at night and most will say driving revenue‚ increasing profitability‚ staying ahead of the competition‚ and retaining customers. For the past year and a half‚ companies in a variety of industries— most notably those involved in the financial services‚ telecommunications‚ travel and tourism industries—have looked to large customer relationship
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Dealing with Data: Using NVivo in the Qualitative Data Analysis Process The decision to use computer software programs for qualitative data analysis is essentially up to the person analyzing the data. There are positives and negatives when using these software programs to analyze data. A researcher in London wanted to find out if using the software package NVivo would be helpful in her data analysis process. The purpose of the study was to consider the difficulties surrounding interrogation
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1. Do you think your school would benefit from installing a customer relationship management (CRM) system? How might it benefit you as a student? How could it benefit your school? Yes. All the advantages from implementing the customer relationship management system will be explained later on from the school’s perspective. Firstly‚ from the student’s point of view‚ we are able to save valuable time due to the increased efficiency of customer (students) service from the school’s administration
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Using ArrayList<ITSystem>‚ Reading and writing Data to/from Files Note: slight changes were made on 11/14 (1 day after this was put up). Specifically‚ the source files are slightly different from the solution to p2. When comparing two ITSystems we are now only concerned with ID. Highlighted text reflects changes made to the assignment. For this assignment‚ we will continue to work with the SysInventory program we developed in the last programming project‚ with a few minor changes/additions. See
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ANALYTICAL CRM HOMEWORK 3 By RAKHI LADDAR (UIN: 622003139) Initially a connection is established. To perform the task of performing data mining through excel first a connection needs to be established to sql server. Server used is infodata.tamu.edu. Classification- Builds a model that describes the class (target) attribute as a function of input attributes. The outcome is a decision tree or a neural network or a logistics regression. Below a series of screen shots‚ using classification
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Finance and Risk Management 180+ Transactional Banking 200+ mBanking‚ eBanking and mPayments © 2011 SAP AG. All rights reserved. Confidential 2 SAP in BFSI in South Asia General Ledger‚ Financial Consolidation‚ Procurement Mobility CRM‚ Business Analytics Human Capital Management Corporate Connectivity Business Analytics Treasury (Asset Management) © 2011 SAP AG. All rights reserved. Confidential 3 Notable Analysts recognize SAP Solutions in Banking FORRESTER
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HL7 eLearning Course Module 2: Data Exchange Standards Learning Objectives: 1. The reader should understand how HL7 messages are transmitted in real time application interfaces. 2. The reader should understand what are Lower Level Protocol (LLP) when discussing the transmission of the HL7 Messages. 1 HL7 eLearning Course Data Exchange Standards • Lower Layer Protocol (LLP) is the most common mechanism for sending unencrypted HL7 message over a local area network‚ such as those found in
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