Baolin Li

In multiple attribute decision‐making (MADM), to better denote complicated preference information of decision‐makers (DMs), picture fuzzy set (PFS) as an expansion of intuitionistic fuzzy set (IFS) has become a powerful tool in the recent years. Meanwhile, to remove the impact of abnormal data and capture the correlations among attributes in MADM issue, we propose the power improved generalized Heronian mean (PIGHM) operators in this paper, which have the merits of both power average (PA) operator and improved generalized Heronian mean (IGHM) operator. Additionally, Hamacher operations as a generalization of Algebraic operations and Einstein operations demonstrate good smooth approximate. Motivated by these, the main purpose is to explore PIGHM operators utilizing Hamacher operations to cope with MADM issue with picture fuzzy information. First, we introduce the Hamacher operations, the normalized hamming distance, and similarity measure of picture fuzzy numbers (PHNs). Second, based on these, two new picture fuzzy aggregating operators (AOs), the picture fuzzy Hamacher weighted power improved generalized Heronian mean (PFHWPIGHM) operator and the picture fuzzy Hamacher weighted geometric power improved generalized Heronian mean (PFHWGPIGHM) operator, are put forward, and some properties and special instances of proposed AOs are also investigated. Third, a new MADM model in terms of the PIGHM AOs is developed. Eventually, a practical MADM example, together with sensitivity analysis and comparative analysis, is conducted to verify the credibility and superiority of the new MADM model.

To better express and handle the increasing complicated fuzzy decision making information, we firstly put forward the concept of multiple-valued picture fuzzy linguistic set (MVPFLS), which is motivated by the advantages of hesitant fuzzy set (HFS), linguistic term set (LTS), and picture fuzzy set (PFS). First, the concepts concerning MVPFLS and the multiple-valued picture fuzzy linguistic element (MVPFLE) are proposed. Second, the operating rules of MVPFLEs on account of linguistic scale functions (LSFs) are given, and the compared functions for MVPFLE are also defined. Third, the traditional generalized Heronian mean (HM) operators capturing the correlation among attributes are extended to multiple-valued picture fuzzy linguistic environment, namely, the multiple-valued picture fuzzy linguistic generalized weighted Heronian mean (MVPFLGWHM) aggregating operator and the multiple-valued picture fuzzy linguistic generalized weighted geometric Heronian mean (MVPFLGWGHM) aggregating operator are proposed, their interesting characteristics and some particular instances are also given. Fourth, the method utilizing the proposed aggregating operators to settle multiple attribute decision making (MADM) issues is provided. Eventually, a practical instance is employed to validate the powerfulness of the new approach, and the sensitivity analysis is performed along with comparative analysis.

In order to take into account quantitative and qualitative information in real complex decision making issue, a multiple-valued neutrosophic uncertain linguistic set (MVNULS) is initially proposed, which includes the uncertain linguistic part and the multiple-valued neutrosophic set (MVNS). Consequently, it has the advantages of them in expressing evaluation information. In the article, we initially define some concepts containing a multiple-valued neutrosophic uncertain linguistic set (MVNULS) and a multiple-valued neutrosophic uncertain linguistic element (MVNULE). Next, we present some basic operational rules regarding Dombi t-conorm and t-norm, which is more flexibility with a general parameter, and introduce a comparison method for multiple-valued neutrosophic uncertain linguistic numbers (MVNULNs). Since the aggregating operator of normalized weighted Bonferroni mean (NWBM) cannot only capture the interrelationship among multiple arguments, but also consider weight vector on each criterion and has the reducibility property, the NWBM operator has gained many attentions of scholars. Hence, in order to deal with the aggregation of MVNULEs, we put forward the multiple-valued neutrosophic uncertain linguistic Dombi normalized weighted Bonferroni mean (MVNULDNWBM) operator on account of Dombi t-conorm and t-norm, and discuss the desirable properties of the MVNULDNWBM operator. Furthermore, we investigate a multiple attribute decision making (MADM) approach in view of the aggregating operator to handle the MADM problem with multiple-valued neutrosophic uncertain linguistic information. Eventually, we conduct a concrete instance to validate the effectiveness and application of the developed approach.

This paper proposes that repatriate’s knowledge transfer is composed of two dimensions: Explicit knowledge transfer and tacit knowledge transfer. The influencing of repatriate’s knowledge transfer on enterprise performance is discussed, and the mediating role of ambidexterity innovation in the above relationships is analyzed. Then, relative assumptions are put forward, and theoretical model is established. Lastly, 156 multinational corporations are selected as study object, and data are collected, bias analysis, descriptive statistic analysis and hierarchical regression analysis are made. The conclusions are got, which are explicit knowledge transfer and tacit knowledge transfer have significant positive effect on exploitative innovation and exploratory innovation, respectively; and explicit knowledge transfer has more effect on exploitative innovation, while tacit knowledge transfer has more effect on exploratory innovation. The findings also indicate that exploitative innovation and exploratory innovation play partial mediation effect on the relationship between explicit knowledge transfer, tacit knowledge transfer and enterprise performance.

The traditional 3 X 3 cell neighborhood used in a focal operation on a raster layer has a square shape that results in a dimensional neighborhood of which the orientation is eventually arbitrary to the physical features represented. This paper presents an experiment using a circular neighborhood to calculate slope gradient. Comparisons of the results from a circular neighborhood with the results from some traditional methods show that (a) for a smooth surface, the result from a circular neighborhood is more accurate than that from a square neighborhood, (b) a circular neighborhood is generally more sensitive to noise in the input DEM than a square neighborhood, and (c) in a validation using field measurements, the circular neighborhood performs better than the square neighborhood when the ratio of user-specified neighborhood size to cell size is high.