Z-number valuation using fuzzy Delphi method for COVID-19 vaccine selection decision in Malaysia

Selection of COVID-19 vaccine among the developing country has received significant attention among the local practitioners since the requirement is vital for every people in the country. In Malaysia particularly, there are two main issues often arising in the selection process; i) what are the criteria to determine the selection of vaccine, and ii) how to deal with the uncertain information in criteria along the selection process. These issues cannot be avoided since the nature of the vaccine itself is vary and diverse in terms of its characteristics. To deal with the first issue, this research came out with the effort to identify the criteria that influenced the decision-makers to make their decision. For the second issue, this research carried out a Z-number valuation approach using fuzzy Delphi method (FDM) in the decision process. A Z-number which is known as a two component where define as Z =(Â, B̂), with the first component  is restriction on the values, while the second component B̂ is a measure of reliability or certainty for the first component (Â). The second component (B̂) in Z-numbers is an advantage to be utilized and the proposed method employs five steps to evaluate the COVID-19 vaccine selection in Malaysia. To show the feasibility of the method, a case study was employed which involved the various backgrounds of COVID-19 experts and practitioners. The results showed that the method has a great approach to deal with the uncertainty elements in the evaluation process. In addition, this research effort has the ability to offer a clear selection procedure for choosing the COVID-19 vaccine in the decision process, particularly in Malaysia context.