Sanjay Mohapatra – författare

​​​The importance of benchmarking in the service sector is well recognized as it helps in continuous improvement in products and work processes. Through benchmarking, companies have strived to implement best practices in order to remain competitive in the product- market in which they operate. However studies on benchmarking, particularly in the software development sector, have neglected using multiple variables and therefore have not been as comprehensive. Information Theory and Best Practices in the IT Industry fills this void by examining benchmarking in the business of software development and studying how it is affected by development process, application type, hardware platforms used, and many other variables.

Information Theory and Best Practices in the IT Industry begins by examining practices of benchmarking productivity and critically appraises them. Next the book identifies different variables which affect productivity and variables that affect quality, developing useful equations that explaining their relationships. Finally these equations and findings are applied to case studies. Utilizing this book, practitioners can decide about what emphasis they should attach to different variables in their own companies, while seeking to optimize productivity and defect density.

​​E-Commerce Strategy: Text and Cases provides the fundamental literature required for graduate students and practitioners to understand electronic commerce. Each chapter provides clearly designed learning objectives and review questions to highlight the major topics and goals. This book covers many of the new innovations and technologies that have been established for e-commerce site development. Unlike similar books, topics such as e-channel adoption, factors affecting e-commerce adoption, and strategy design are reviewed in greater depth. Additionally, the book examines areas not normally covered like open source, online research, and peer-to-peer systems.

E-Commerce Strategy: Text and Cases is divided into two parts. Part 1 examines the evolution of e-commerce, analyzes different sectors such as B2B and m-Commerce, and explores the challenges they face. Case studies of well known companies reinforce the concepts learned to demonstrate both successes and failures in the field. Part 2 deals with developing strategies in e-Commerce and looks at future trends including Web 2.0. Overall, the useful guidelines provided should prove valuable to students and researchers in the field.

Stock market manipulation is detrimental to traders and corporations, causes unnecessary price fluctuations, and only benefits financial criminals. The research presented here determines an appropriate model to help identify stocks witnessing activities that are indicative of potential manipulation through three separate but related studies.

In Developing an Effective Model for Detecting Trade-Based Market Manipulation, classifiers based on three different techniques namely discriminant analysis, a composite classifier based on Artificial Neural Network and Genetic Algorithm and support Vector Machines is proposed. The proposed models help investigators, with varying degree of accuracy, to arrive at a shortlist of securities which could be subject to further detailed investigation to detect the type and nature of the manipulation, if any.

Following a fluid outline, Developing an Effective Model for Detecting Trade-Based Market Manipulation, introduces the topic, explores the aims and scopes of the research, before delving into the data and modelling to explore their application to the stock market to detect price manipulation.