Author Description

Business intelligence (BI) is considered as the process of turning data into information and then into knowledge allowing decision makers to tune their actions according to the company strategy (Golfarelli, Rizzi, and Cella, 2004). BI is also one of the techniques to improve qualitative and quantitative value of the knowledge available to decision makers (Cody, Kreulen, Krishna, and Spangler, 2002). Hence, BI can contribute to decision making (Ishikawa and Nakagawa, 2013). The process involves the application of research methods, models, and approaches to various domain problems. The field of management has a drive for an increasing need for data analysis (Moutinho and Huarng, 2012). The demonstration of how the process can be applied to assist decision making is interesting to many practitioners. However, to obtain better quality of information to assist better decision making, the development of new research methods, models, and approaches is also very important, which may involve creating new methods, refining, or integrating existing methods. Hence, the need for introducing the development is also critical. to that end, this e-book is to offer a collection of papers focusing on both perspectives, First, the development of new research methods, models, and approaches includes proposing a new semi-parametric framework, proposing a new path Philips curve, proposing a new regime switch forecasting model, proposing a quantile regression forecasting model, integrating both quantitative (questionnaires) and qualitative (interview), and integrating the Modigliani-Miller theorem and stock repurchases strategy. Second, the application the existing research methods to various problems includes investigating optimal decision methods, applying Analytic Hierarchy Process, applying soft computing technique and fuzzy statistics, and applying statistics to fuzzy data. The purpose is to model the problem better, to understand the problem better, to forecast better so as to assist