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Energy conservation and emission reduction (ECER) has become an indispensable trend of green life. How to choose a suitable technology for ECER under complex decision-making scenarios has become a key issue faced by traditional industrial enterprises. In this paper, a new integrated decision-making framework is established for technology-selection problems. Firstly, to describe complex linguistic information more accurately and reduce information loss, this framework employs the double hierarchy hesitant fuzzy linguistic term sets (DHHFLTSs) to describe the performance of alternatives. To avoid data redundancy and simplify the computation, we improve the operations of double hierarchy hesitant fuzzy linguistic elements (DHHFLEs) and propose a new comparison method for DHHFLEs. Secondly, based on the proposed normalized projection-based difference measurement, a novel method is proposed to derive the weights of experts regarding each criterion, the group decision-making method based on the best-worst method is also utilized to derive the criteria's weights via consistent pairwise comparisons. Further, an integrated generalized TODIM (an acronym in Portuguese of interactive and multiple attribute decision making)-ELECTRE II (Elimination and Choice Translating Reality II) method is established to rank alternatives, which has the advantages of dealing with the non-compensatory problem of criteria and considering risk-aversion behavior of experts simultaneously. Subsequently, a case study of emission-reduction technology investment is provided to manifest the practicality and reliability of the given framework. Finally, the preponderance and effectiveness of the proposed method are illuminated through a comparative analysis with several existing representative methods. [ABSTRACT FROM AUTHOR]

In present-day society, government public service outsourcing has become an irreversible trend due to the gradually increasing public pursuit of service quality and efficiency. To better meet the needs of the public and effectively improve the quality of service, it has been a crucial issue for government departments to choose the most desirable one from a series of public service outsourcers (PSOs) with distinct characteristics. In this paper, to deal with such decision problems, we propose the improved elimination and choice translating reality (ELECTRE) II method with unknown weight information under the double hierarchy hesitant fuzzy linguistic (DHHFL) environment to accurately and effectively select the best PSO. Firstly, aiming at the shortcomings of the original comparison method for double hierarchy hesitant fuzzy linguistic elements (DHHFLEs), we define the hesitant deviation degree (HDD) for DHHFLEs and, based on this, further propose a new comparison method for comparing DHHFLEs more reasonably. Secondly, inspired by the classical power average (PA) operator proposed by Yager, a new method is introduced to determine the weights of experts with respect to each attribute, based on the support degree between attributes. Afterwards, an improved ELECTRE II method is proposed to address the problem of PSO selection. A numerical case about e-government outsourcer selection is given to demonstrate the enforceability of the method. Finally, comparisons between previous methods and our method are carried out to illustrate the effectiveness and strengths of the proposed method. [ABSTRACT FROM AUTHOR]