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Managers often have to face kinds of decision-making problems in which a suitable investment alternative has to be evaluated and selected (Zhou et al., 2019; Yan et al., 2017; Rostamzadeh et al., 2017). Such a choice maybe related, for instance, to the technology choose for product development or machine selection for a manufacturing process (Frank et al., 2013). This kind of investment alternatives can be considered a multiple attribute decisionmaking (MADM) problem as it involves a variety of attributes that should be taken into account from finite feasible schemes based on the assessment information provided by decision makers. Due to the uncertain objects and ambiguous human thinking, sometimes it is impossible for decision makers to give all the evaluation values of attributes by exact numbers. The definition of fuzzy set is firstly introduced by Zadeh (1965) to address the uncertainty and ambiguity, which has been widely used in various domains.

The statistical process control (SPC) is widely used in industry. Its aim is to achieve proces stability and improve capability through the reduction of variability and it is included for example in the Six Sigma or Lean Six Sigma methodologies. The control of attribute data represents a considerable part of it. Until recently, the same approach was used to monitor variables or attributes data. In this approach, subgroups of items are taken from a process and sample characteristics are plotted in a control chart to see whether their variation is only random or whether it is affected by an assignable cause. The presence of such cause is indicated by exceeding the control limits that are based on the sample characteristic distribution.

Knowledge is certainly one of the most important assets possessed both by individuals and by societies. In (substantial) part of the World, knowledge of individuals is obtained via a formal education in an educational system divided into subsequent several stages (usually pre-primary, primary, secondary, and tertiary education). Nowadays, populations’ costs of formal public education in the majority of countries constitute a significant portion of national wealth, often exceeding 5% of a gross domestic product. On average, World’s education costs reached 4.7% of the World’s GDP in 2013, according to the World Bank (2017). The costs of private education and especially the costs of tertiary education at the top universities in the USA, Canada, UK, or China are also considerably high.

Health care economists estimate that 40-50% of annual cost increases can be traced to new technologies or the intensified use of old ones (Callahan, 2008). However, any limitation of their application is massively criticized as unethical. Patients (supported by journalists) believe that new expensive technology will speed-up their treatment and miraculously enhance their quality of life, while physicians are fascinated by fanciful possibilities of state-of-the-art devices. Nevertheless, due to limited resources of health care, each particular utilization of a medical device should be put to the test of the clinical effectiveness and cost-effectiveness (Markiewicz, van Til, & Ijzerman, 2014; Rosina et al., 2014). The typical approach used above all in drugs is to calculate cost-effectiveness when the technology is in routine use.

Motivation research has a long history of considering employee motives and needs, and it is still popular. To find the reason, it is not necessary to look for a long time. Numerous studies have shown that employees could be the most valuable asset that organizations have. Employees, with their knowledge, skills, abilities, and work attitudes, influence how efficiently resources and means are used. Kazdová (2012) says that the employee who is motivated speaks about the firm positively, sees his/her future in the firm, and makes an extra effort which leads to the improvement of organizational outputs. According to Swift, Balkin, and Matusik (2010), employee motivation influences knowledge sharing in the organization, among other things. If the employee is motivated, he/she is more willing to share knowledge (Hau, Kim, Lee, & Kim, 2013).