Language : English
Published : 2013-11-01
Pages : 247
For courses in Sustainable Marketing or as a supplement to marketing courses that include sustainability as a focus. A lasting approach to marketing. As the engine that drives the global economy, marketing leaves an enormous footprint on the environment and society. To help readers make a lasting impression in their marketing efforts, Martin/Schouten provides the concepts behind valuable-and lucrative-sustainable marketing strategies.
Research Methods for Business Students has been fully revised for this seventh edition and continues to be the market-leading textbook in its field, guiding hundreds of thousands of student researchers to success in their research methods modules, research proposals, projects and dissertations. So, if you’re thinking …’How do I choose my topic?’ ‘I’m confused by all these different philosophies’ ‘I need to collect my data; what do I do first?’ ‘When and what do I need to write? …then, open this book to discover: * Regular checklists and ‘Progressing your research project’ sections to give you step-by-step practical guidance on the process * A glossary of clear definitions for 600 research terms * Cases and examples of students’ and academics’ research and topical news articles illustrating research in practice * Detailed chapters on choosing your topic, reviewing the literature, understanding philosophies, research design, access and ethics, secondary data, data collection and analysis, and writing about and presenting your research Don’t forget to visit www.pearsoned.co.uk/saunders where you can use online tutorials on research software, such as IBM SPSS Statistics and NVivo, test yourself with hundreds of multiple choice questions, analyse over 60 further case studies, and learn how to search the Internet more efficiently and effectively with our Smarter Online Searching guide! Start your project with confidence and complete it with success! Mark Saunders is Professor of Business Research Methods at The Surrey Business School, University of Surrey. Philip Lewis was a Principal Lecturer and Adrian Thornhill was a Head of Department, both at the University of Gloucestershire.
This book is wholly dedicated to the art of exploratory spreadsheet modeling. Real problems that readers encounter on a day-to-day basis are presented, with the aim of helping them derive applicable principles and link principles to practice.
Users of this book will find it a refreshing learning guide and handy reference resource. It offers 101 spreadsheet exercises and tools, including a chapter featuring another 101 business challenges that readers can practice as modeling projects. Introduced for the first time in this third edition is a set of Discovery Points, 46 in total. They are included to enlighten readers and instructors on the underlying exploratory thinking employed in the exercises.
Though the book can be used with different versions of Microsoft Excel, LibreOffice and OpenOffice Calc, and other spreadsheet application software, this edition only presents Excel 2010-13 spreadsheet features and functions, and Visual Basic for Application in its appendices.
The notes for older Excel versions, and OpenOffice Calc and Basic from the earlier editions, and the newly added LibreOffice Calc and Basic are now found in a new Online Learning Center that accompanies this book. Completed spreadsheet workbooks in the different spreadsheet versions are also provided there.
This way, the book should remain helpful for any person, whether a novice, beginner, or expert, to learn business modeling using basic and advanced spreadsheet features, as well as macro programming.
Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms. Quotes This book provides a comprehensive coverage of important data mining techniques. Numerous examples are provided to lucidly illustrate the key concepts. -Sanjay Ranka, University of Florida In my opinion this is currently the best data mining text book on the market. I like the comprehensive coverage which spans all major data mining techniques including classification, clustering, and pattern mining (association rules). -Mohammed Zaki, Rensselaer Polytechnic Institute
Praise for the Second Edition ” full of vivid and thought-provoking anecdotes…needs to be read by anyone with a serious interest in research and marketing.” Research Magazine “Shmueli et al. have done a wonderful job in presenting the field of data mining – a welcome addition to the literature.” ComputingReviews.com “Excellent choice for business analysts…The book is a perfect fit for its intended audience.” Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization ” extremely well organized, clearly written and introduces all of the basic ideas quite well.” Robert L. Phillips, Professor of Professional Practice, Columbia Business School Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft(R) Office Excel(R) add-in XLMiner(R) to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: * Real-world examples to build a theoretical and practical understanding of key data mining methods * End-of-chapter exercises that help readers better understand the presented material * Data-rich case studies to illustrate various applications of data mining techniques * Completely new chapters on social network analysis and text mining * A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint(R) slides * Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology.