This book is dedicated to mixed (integrated, hybrid, combined) intelligent systems for project evaluation and indicates contemporary challenges resulting from the current state of knowledge in the fields of mixed methods studies, knowledge engineering, Artificial Intelligence (AI), project management, and evaluation based on business and management sciences. Dealing with this kind of research problem is justified by thinking about the further development of theory and practical achievements in research concerning intelligent systems for project evaluation.
The origin of this book is the result of identifying the need and the opportunity to continue conducting interdisciplinary research concerning the development of new models of comprehensive project evaluation systems. The correct functioning of evaluation systems directly influences the efficient and effective planning and implementation of various types of project and organizational achievement objectives. Projects, in fact, play an increasingly important role in realizing the goals of modern business and non-commercial organizations, where both the projects and their evaluation processes are complex, unique and have a multifaceted nature.
Since evaluation systems should have a multidimensional and comprehensive nature, one ought to use different methods and systems to ensure the integration of quantitative and qualitative criteria. There are no simple answers to research questions concerning the correctness and value of contemporary projects; no single method, system or approach can decipher the inherent complexities, and several quantitative and qualitative methods, used simultaneously, are needed (American Evaluation Association 2009). Mixing and matching methods and systems in evaluation procedures is a rule rather than an exception (Williams 1999).
In the most popular definition, mixed methods research is a process of integration of both qualitative and quantitative methods and systems of data collection and analysis in order to better understand research goals (Plano Clark and Ivankova 2015). Studies conducted demonstrate that the use of mixed methods research together with quantitative and qualitative approaches in research processes leads to the creation of a more holistic image of multifaceted research than conventional analytical methods (Brannen 2005). This is particularly desirable in complex evaluation studies. The increased demand for mixed evaluation methods can be illustrated by the raising of awareness among evaluators concerning complexity issues and, therefore, the rapid increase in interest in this topic (Mertens 2017). The popularity of mixed research is evident through the formation of special interest groups, professional associations, the production of journal articles, books and conference papers, and the use of the terms âthird methodological movementâ, âthird research paradigmâ and ânew star in the social science skyâ (Creswell and Plano Clark 2017).
Mixing various evaluation methods and systems represents one of the alternative directions of project evaluation systems in their development toward complex and comprehensive solutions. Models based on several methods and systems can improve the quality of evaluation results and lead to more objective research. Therefore, studies related to the search for new models that contribute to the improvement of previously known evaluation systems and combine several methods are justified. In particular, it may be useful to combine project evaluation models that utilize both traditional evaluation systems and systems based on AI and knowledge engineering (Grzeszczyk 2013).
There is a need to conduct interdisciplinary research, beyond conventional academic boundaries, within combined models from several scientific disciplines and to use a variety of methods and systems applications in solving complex project evaluation problems. This type of approach is in line with the interdisciplinary nature of the comprehensive project evaluation problem and refers to the increasingly popular idea of science without borders. One should use many academic disciplinary approaches to solve project evaluation problems, drawing on business, management and social sciences. Within the framework of interdisciplinary methodological research, there is a need to investigate methods known within several established disciplines used for the modeling and implementation of mixed intelligent systems for project evaluation.
The key assumptions underlying the research presented are as follows:
- 1.Interdisciplinary study, conducted on the basis of business and management sciences, concerning the development of new models of comprehensive project evaluation systems and the combined use of several methods, including both hard and soft methodologies, allows for multidimensional research perspectives and reduces the disadvantages of methods and systems used separately.
- 2.Intelligent and classical systems of decision-making, systems approaches, Integral Theory and innovative technologies based on AI and Knowledge Engineering as new factors within project management research can lead to significant opportunities for the development of new, comprehensive project evaluation systems.
The potential development of models for project management and evaluation can be enhanced by the continuous verification and enrichment of the degree of differentiation of methods and systems as well as their improvement, in order to increase the accuracy of decisions taken. Application of AI and knowledge engineering systems, in addition to classic solutions, in integrated systems justifies the use of the term âmixed intelligent systemsâ.
The main research objective of this study is to investigate the needs and possibilities of using mixed intelligent systems in project management and evaluation and also to propose selected model solutions in this area.
The structure of the book results from the key assumptions and main objective of this scientific research. The book consists of seven chapters. After the introduction, Chap. 2 presents basic issues related to project evaluation. Chapter 3 deals with quantitative evaluation methods while Chap. 4 focuses on qualitative methods. Selected problems that concern sy...