Fuzzy analytical approach to partnership selection in formation of virtual enterprises

Mikhailov, Ludmil

doi:10.1016/s0305-0483(02)00052-x

Cited by 244 publications

(136 citation statements)

References 24 publications

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“…The above membership function is often employed in the FPM to derive the priority weights from an IVMPR (Mikhailov 2002(Mikhailov , 2003(Mikhailov , 2004Chen and Xu 2015). However, there exist some shortcomings when using Eq.…”

Section: Letmentioning

confidence: 99%

“…It takes the constraints of priority weights as fuzzy constraints and constructs the membership functions of fuzzy constraints to express DM's satisfaction. By maximizing DM's satisfaction degree, the fuzzy program is established to determine the priority weights from IVMPR (Mikhailov 2002(Mikhailov , 2003(Mikhailov , 2004Chen and Xu 2015).…”

Section: Shortcomings Of the Fpm For Deriving The Priority Weights Frmentioning

confidence: 99%

“…To derive the priority weights from IVMPR ( ) ij n n a × = % A , the classic FPM (Mikhailov 2002) regards Eq. (3) as the fuzzy inequalities:…”

Section: Shortcomings Of the Fpm For Deriving The Priority Weights Frmentioning

confidence: 99%

“…(b) Many studies (Mikhailov 2002(Mikhailov , 2003(Mikhailov , 2004Chen and Xu 2015) applied the convex probability distribution in probabilistic methods to fuzzy/multiplicative preference relation. Especially, the triangular or trapezoidal fuzzy judgments are usually employed in the FPMs (Mikhailov 2002(Mikhailov , 2003(Mikhailov , 2004Chen and Xu 2015).…”

Section: Approaches To Solving the Constructed Intuitionistic Fuzzy Pmentioning

confidence: 99%

“…It was developed originally by Mikhailov (2002). He constructed a fuzzy programming model to derive priority weights from an IVMPR and thus designed a fuzzy analytical approach to solving partnership selection problems.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations

Wan

Wang

et al. 2016

Fuzzy Optim Decis Making

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Section: Letmentioning

confidence: 99%

Section: Shortcomings Of the Fpm For Deriving The Priority Weights Frmentioning

confidence: 99%

“…To derive the priority weights from IVMPR ( ) ij n n a × = % A , the classic FPM (Mikhailov 2002) regards Eq. (3) as the fuzzy inequalities:…”

Section: Shortcomings Of the Fpm For Deriving The Priority Weights Frmentioning

confidence: 99%

Section: Approaches To Solving the Constructed Intuitionistic Fuzzy Pmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations

Wan

Wang

et al. 2016

Fuzzy Optim Decis Making

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Exploring networks of proximity for partner selection, firms' collaboration and knowledge exchange. The case of clean‐tech industry

Marra

Carlei

Baldassari³

2019

Bus Strat Env

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Nowadays scholars widely recognize that know‐how, capabilities and knowledge needed to generate innovations often reside outside the firm, start‐ups are a valuable source, and collaborative networks are a fundamental strategy for innovation. This is true especially for the clean‐tech sector, which is characterized by the continuous search for innovative solutions and technological advancements. The purpose of the paper is to provide a methodological support for the screening of potential partners based on network analysis and, then, help firms to select them for collaboration and knowledge exchange. The methodology can be easily adopted by managers and executives to identify firms to monitor with greater attention for future investments. The analysis is on a dataset of 4,782 clean‐tech companies operating worldwide. Results highlight that energy companies looking for external sources could investigate their network of business proximity if they intend to specialize in a defined field and/or collaborate with similar partners, while they could explore their network of strategic proximity if they intend to diversify their businesses, that is cooperating and exchanging knowledge with firms with distant but complementary capabilities and resources.

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An Application of the Fuzzy ELECTRE Method for Academic Staff Selection

Rouyendegh

Erkan

2012

Hum Ftrs & Erg Mfg Svc

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There are various methods regarding staff selection in different fields. Thanks to the increasing improvements in the field of education, universities around the world tend to demand high ‐quality and professional academic staff. Staff selection is a multi‐criteria decision‐making processes, and of strategic importance for most universities. This study deals with actual application of academic of staff selection using the opinion of experts to be applied into a model of group decision ‐ making called the Fuzzy ELECTRE (Elimination Et Choix Traduisant la REaite) method. There are ten qualitative criteria for selecting the best candidate amongst five prospective applications. © 2012 Wiley Periodicals, Inc.

show abstract

Fuzzy analytical approach to partnership selection in formation of virtual enterprises

Cited by 244 publications

References 24 publications

An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations

An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations

Exploring networks of proximity for partner selection, firms' collaboration and knowledge exchange. The case of clean‐tech industry

An Application of the Fuzzy ELECTRE Method for Academic Staff Selection

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