A Bibliometric Analysis of Research on Multiple Criteria Decision Making

Yu, Dejian; Wang, Wanru; Zhang, Wenyu; Zhang, Shuai

doi:10.18520/cs/v114/i04/747-758

Cited by 70 publications

(47 citation statements)

References 37 publications

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“…Table 5 shows a pair-wise comparison matrix which is created according to the Saaty's 9 pair comparison scale shown in Table 2 based on the market survey of 100 computer users. In this matrix each and every criterion is compared [31] with the other criteria to find out the relative importance's among each other. For example, when processor is compared to processor itself, value 1 is allotted in the cell a11 according to Satty's scale [3] which states that 1 stands for the equal importance.…”

Section: Methodsmentioning

confidence: 99%

Application of Simple Average Weighting Optimization Method in the Selection of Best Desktop Computer Model

Mitra¹,

Goswami²

2019

Adv. J. Grad. Res.

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Multi-Criteria Decision Making (MCDM) is one of the most emerging concepts in today’s world which enables a decision maker to select the best strategies among different available alternatives. MCDM technique helps to remove the biasness and confusion while selecting a product or process. In recent few years different MCDM methodologies finds wide area of applications in industries as well as in our daily life. In this paper, such one type of application is broadly described. One example is taken from our daily life, which is generally faced by most of the students while purchasing a desktop computer. The main objective of this paper is to select the best desktop computer models among five different models actual available in the market having different configurations. For this analysis, 100 computer users have been surveyed to know their relative preferences and choices, which of the computer specifications is most important to them. For this present analysis few numbers of criteria have been considered and also there are number of sub-criteria within each criterion (for example, the processor may be different for different models like I3, I5, I7 etc.). The MCDM methodology which is adopted for this selection process is known as Simple Average Weighting (SAW) method.

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Section: Methodsmentioning

confidence: 99%

Application of Simple Average Weighting Optimization Method in the Selection of Best Desktop Computer Model

Mitra¹,

Goswami²

2019

Adv. J. Grad. Res.

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“…In the literature, there are numerous combinations of the weighting and evaluation methods that form various hybrid methods to deal with uncertainty and vagueness in decision-making [19]. The fuzzy set, rough set, grey set as well as probabilistic models, such as evidential reasoning, are used as the main approaches to account for uncertainties.…”

Section: Hybrid Mcdm Methodsmentioning

confidence: 99%

Grey Regulatory Focus Theory Weighting Method for the Multi-Criteria Decision-Making Problem in Evaluating University Reputation

Esangbedo

Bai

2019

Symmetry

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Evaluating the reputation of higher institutions is important as a benchmark for the continuous development of universities. In multi-criteria decision-making (MCDM), the estimation of the criteria weight is significant in improving the accuracy of the evaluation results. However, criteria weights assigned by decision makers (DMs) can be inaccurate when not measured from the orientations from which the DMs pursue their decision goals. This paper combines the grey system theory (GST) and regulatory focus theory (RFT) in estimating the weights of criteria by measuring the promotional and prevention focus orientations of the DMs and representing it as grey numbers. In this paper, we showed not all weight measurements from the DMs are symmetrical. In essence, to improve the accuracy of the MCDM weights, the grey regulatory focus theory (GRFT) weighting method is proposed to estimate the weights of an MCDM problem as well as aggregating the weights of the group DMs, thereby overcoming the limitation of a single orientation measurement. Furthermore, the GRFT weighting method is applied in ranking four universities in Xi’an city of China from a sample data from 1,200 students. The most reputable university is consistent with the other ranking indexes in the literature.

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“…In addition, those types of narrative literature review also carry some degrees of limitation especially those involving longitudinal cases conducted over a long period of time. Consequently, caution should be applied when interpreting the results, except for a few exceptions (Blanco-Mesa, Merigo, & Gil-Lafuente, 2017;Bragge, Korhonen, Wallenius, & Wallenius, 2010;Qaiser, Ahmed, Sykora, Choudary, & Simpson, 2017;Yu, Wang, Zhang, & Zhang, 2018). Thus far, existing studies have not been able to indicate with details, how research on SD had evolved over the years, which this study aims to address.…”

mentioning

confidence: 93%

“…These bibliometric methods have been consistently employed to explore the intellectual structure of strategic management (Ferreira, Fernandes, & Ratten, 2016;Nerur, Rasheed, & Natarajan, 2008;Ramos-Rodríguez & Ruíz-Navarro, 2004;Ronda-Pupo & Guerras-Martin, 2012). Earlier bibliometric literature had mainly focussed on fuzzy decision making (Blanco-Mesa et al, 2017), multiple criteria decision making (Bragge et al, 2010;Yu et al, 2018), and the decision support system (Qaiser et al, 2017). Seminal bibliometric analyses have been used by scholars (Yu et al, 2018;Blanco-Mesa et al, 2017;Ferreira et al, 2016;Steptoe-Warren et al, 2011;Elbanna & Younies, 2008;Rajagopalan et al, 1993) to review literature on SD.…”

mentioning

confidence: 99%

“…Earlier bibliometric literature had mainly focussed on fuzzy decision making (Blanco-Mesa et al, 2017), multiple criteria decision making (Bragge et al, 2010;Yu et al, 2018), and the decision support system (Qaiser et al, 2017). Seminal bibliometric analyses have been used by scholars (Yu et al, 2018;Blanco-Mesa et al, 2017;Ferreira et al, 2016;Steptoe-Warren et al, 2011;Elbanna & Younies, 2008;Rajagopalan et al, 1993) to review literature on SD. However, digressing slightly from this, the current review aims to provide a perspective of the continuity, and a more updated and integrative point of view on the research on SD, as compiled from past studies.…”

mentioning

confidence: 99%

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Intellectual Structure and Scientific Evolution of Strategic Decision in the Field of Business and Management from 1971 to 2018

Patria

Wahyuni

Kusumastuti

2019

AJBA

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Manuscript type: Review paper Research aims: This study aims to analyse the published works of strategic decision in business and management which have had the greatest impact and evolutionary scientific trend within the intellectual sphere. Drawing from the integrative perspective, this study attempts to: (i) investigate the intellectual structure of earlier works so as to analyse the evolution of strategic decisions; (ii) examine the evolutionary scientific trends, and (iii) identify some implications for future research in this area. Design/Methodology/Approach: This study generates its analysis based on the following bibliometric tools: (i) multidimensional data analysis using the Sankey Diagram, (ii) visual network and heat map analysis using the VOSviewer, and (3) strategic diagrams and evolution maps using the SciMAT. The methodology is based on the bibliometric technique of citation and co-citation analyses which are scientifically applied to a sample of 1,218 articles published in leading management and business journals over a period of 48 years, from 1971 to 2018.

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A Bibliometric Analysis of Research on Multiple Criteria Decision Making

Cited by 70 publications

References 37 publications

Application of Simple Average Weighting Optimization Method in the Selection of Best Desktop Computer Model

Application of Simple Average Weighting Optimization Method in the Selection of Best Desktop Computer Model

Grey Regulatory Focus Theory Weighting Method for the Multi-Criteria Decision-Making Problem in Evaluating University Reputation

Intellectual Structure and Scientific Evolution of Strategic Decision in the Field of Business and Management from 1971 to 2018

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