 Thinking Out of the Box. Non-typical Research Methods in BusinessKinaz Al Aytouni () and
Kinan M. Naddeh ()
A chapter in Modernizing the Academic Teaching and Research Environment, 2018, pp 127-160 from Springer Abstract: Abstract After discussing statistical techniques for data selection, collection, coding, manipulation, summarizing and presentation, this chapter describes one of some relatively new research methods in business, which are non-typical, non-statistical in nature. Artificial Neural Networks (ANNs), case-based reasoning, fuzzy logic and genetic algorithms are advanced techniques that show promises as enablers to solve some difficulties that may lie in analyzing and synthesizing complex systems, which include large quantities of data from several different sources into a coherent research model. Raising the idea up of discovering un-noticed observations or data in front of a researcher is for a purpose. One of the new techniques proposed in this chapter, like data mining, rely on discovering unobserved or unnoticed patterns in the already available data and data sources. This chapter will focus on using ANN method, what is it, who will use it, why and how to use it. The chapter ends by presenting the future trend in using this method, which is the combination among typical and non-typical methods. Date: 2018 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-319-74173-4_8 Ordering information: This item can be ordered from DOI: 10.1007/978-3-319-74173-4_8 Access Statistics for this chapter More chapters in Progress in IS from Springer |
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