Z-Delphi: A Z-Number-Based Delphi Technique for Technological Forecasting to Reduce Optimism/Pessimism Bias in Experts’ Convergent Opinions

Abstract

AbstractThe Delphi technique is an indispensable instrument for technology forecasting. The method is, however, limited by ambiguity aversion, uncertainty, and statistical optimism/pessimism bias. To address the aforementioned limitations, we have proposed a fuzzy Delphi technique based on Z-numbers in this paper, as Z-numbers offer an effective framework to simulate human thinking. We generated basic probability assignments (BPAs) from the experts’ responses, considered statistical dispersion using Grey Clustering, and then developed Z-numbers. The proposed method is flexible and can be applied to forecast technological aspects based on subjective judgments. We consulted with 11 experts to forecast water-saving technology for dairy plants. Entropy was used to compare the proposed method to other fuzzy Delphi approaches. Compared to other fuzzy Delphi methods, we discovered that the proposed approach registers the lowest uncertainty. The proposed study suggests that fuzzy Delphi with reduced uncertainty can be highly impactful in critical fields like sustainable production. In the end, we have discussed the future research directions of the proposed study.