The fuzzy logic method for innovation performance measurement

Brusakova, I. A.; Kosuhina, M. A.

doi:10.1109/scm.2015.7190487

Cited by 7 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Shown in this article way of thinking and methodologically it generated algorithm is premised on the dialectical opposites [7] -the existing level of individual business development and calls for the integration of business processes specific test centers and laboratories. It should be noted that this approach to consider "specific cases" is gaining more and more widely accepted in all areas of modern economic and managerial science [8]- [11]. In addition for establishing the algorithm were used the principles laid down in the state standards of the Russian Federation [12], [13], the general methods of scientific research, typical of logical positivism and the heritage of Ernst Mach philosophy of science [14].…”

Section: Methodological Foundation Of the Algorithm Constructionmentioning

confidence: 99%

Applied economic model development algorithm for electronics company

Mikhailov

2017

SHS Web Conf.

View full text Add to dashboard Cite

Abstract. The purpose of this paper is to report about received experience in the field of creating the actual methods and algorithms that help to simplify development of applied decision support systems. It reports about an algorithm, which is a result of two years research and have more than one-year practical verification. In a case of testing electronic components, the time of the contract conclusion is crucial point to make the greatest managerial mistake. At this stage, it is difficult to achieve a realistic assessment of time-limit and of wage-fund for future work. The creation of estimating model is possible way to solve this problem. In the article is represented an algorithm for creation of those models. The algorithm is based on example of the analytical model development that serves for amount of work estimation. The paper lists the algorithm's stages and explains their meanings with participants' goals. The implementation of the algorithm have made possible twofold acceleration of these models development and fulfilment of management's requirements. The resulting models have made a significant economic effect. A new set of tasks was identified to be further theoretical study.

show abstract

Section: Methodological Foundation Of the Algorithm Constructionmentioning

confidence: 99%

Applied economic model development algorithm for electronics company

Mikhailov

2017

SHS Web Conf.

View full text Add to dashboard Cite

show abstract

“…Apart from the work of Gill and Singh [20], there are several cases in the literature where fuzzy logic was used to predict performance. These cases include but not limited to Gill and Singh [21], Li et al [22], Beikkhakhian et al [23], Brusakova and Kosuhina [24], Barkana et al [25], Bray et al [26], Kumar and Vaidehi [27], Balasubramanian et al [28], Srinivasan and Raajarajan [29], etc. SCOP methodology differs from these because in the methodology transfer function parameters are the fuzzy variables.…”

Section: Introductionmentioning

confidence: 99%

Notes on procedure for the development of fuzzy rules in SCOP methodology

Nwobi-Okoye

2019

Sādhanā

View full text Add to dashboard Cite

The lack of statistical foundations among other shortcomings of existing methods of measuring efficiency necessitated the development of a new method called, Systems Coefficient of Performance Methodology (SCOPM). One key feature of SCOP methodology is the use of fuzzy logic to express complex efficiency measurement parameters into linguistic variables understandable by non experts and the general public. In this research note, the procedure for development of membership functions for the fuzzy logic aspect of SCOPM modeling was standardized and presented. A thorough analysis of fuzzy logic modeling which is at the heart of SCOPM was done. Real life examples and case studies are used to highlight the practical applications and utility of the methodology. The study gives a deep insight into the strengths of SCOP as an efficiency measurement method and its superiority over other efficiency measurement methods like, Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA), etc. Finally, a guide to practitioners on implementation of SCOPM as well as future research direction for academics and researchers is presented.

show abstract

The innovation performance measurement as a crucial determinant of technologically advanced industrial enterprises management

Kossukhina

2016

2016 IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

View full text Add to dashboard Cite

In the current economic conditions the innovation performance measurement is a driving force of innovation system development of technologically advanced industrial enterprises. The aim of the article is to review different approaches to innovation performance measurement and problems associated with their measurements, to provide a system of fuzzy inference for solving the problem of obtaining guidance of innovation performance measurement.

show abstract

The fuzzy logic method for innovation performance measurement

Cited by 7 publications

References 3 publications

Applied economic model development algorithm for electronics company

Applied economic model development algorithm for electronics company

Notes on procedure for the development of fuzzy rules in SCOP methodology

The innovation performance measurement as a crucial determinant of technologically advanced industrial enterprises management

Contact Info

Product

Resources

About