Izvorni znanstveni članak
https://doi.org/10.1080/1331677X.2021.1875255
A multidimensional decision with nested probabilistic linguistic term sets and its application in corporate investment
Xinxin Wang
Zeshui Xu
Qiang Wen
Honghui Li
Sažetak
With the rapid development of information, decision making
problems in various fields have presented multidimensional, complex and uncertain characteristics. Nested probabilistic-numerical
linguistic term set (NPNLTS) is an effective tool to describe complex information due to the nested structure and diverse variables. This paper extends the concept of NPNLTS, and defines an
improved form, i.e., nested probabilistic linguistic term set
(NPLTS), and then proposes a novel VIKOR method with nested
probabilistic linguistic information to solve the model. Within the
context of empirical corporate finance, a case study related to
corporate investment decision is presented and handled by the
novel VIKOR method. After that, comparative analysis is carried
out considering other decision-making methods, decision coefficient in VIKOR, and weights of attributes. As a result, the proposed method not only provides a rational and effective solution,
but also reveals the rule in the case when decision coefficient
and weights of attributes change, respectively. Finally, we discuss
the proposed method from the theoretical and application
aspects with a view to guiding future research. To a certain
extent, this study provides a new decision environment to deal
with multidimensional problems.
Ključne riječi
Nested probabilistic linguistic term set; VIKOR; multidimensional decision; corporate investment
Hrčak ID:
301662
URI
Datum izdavanja:
31.12.2021.
Posjeta: 125 *