Fuzzy VIKOR approach for selection of big data analyst in procurement management

Bag, Surajit

doi:10.4102/jtscm.v10i1.230

Cited by 16 publications

(7 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…VIKOR is known for its computational simplicity and solution accuracy [7,19]. The focus of this method is to select and rank a set of alternatives based on the compromised solutions for a problem with conflicting criteria to assist a decision-maker in taking an optimized decision in their final course of action.…”

Section: Vikor Methodsmentioning

confidence: 99%

Optimizing Service Quality Management of the Bus Rapid Transport System in Lagos Using the Multi-Criteria Decision Analysis

ADEBIYI¹,

AKINRINMADE²,

AMOLE³

2022

SJSUT.ST

View full text Add to dashboard Cite

Evaluation of Bus Rapid Transportation (BRT) based on service quality criteria and customer satisfaction can never be overemphasized due to its derivative, such as optimizing the performance of the transportation industry. Thus, this study employs the multi-criteria decision-making (MCDM) method for the evaluation of service quality and customer satisfaction of the BRT system in Nigeria using the fuzzy analytical hierarchy process (FAHP) and visekriterijumska optimizacija i kompromisno resenje (VIKOR), which are components of multi-criteria optimization and compromise solution to evaluate notable factors responsible for the user’s perspective. Research design is quantitative and analytical in nature through a survey of experts who are users of BRT services. Samples were drawn through a multi-stage sampling procedure and a total of 402 copies of questionnaires were administered to BRT users based on their experience with the system. Hence, VIKOR and FAHP methods are applied to analyse data retrieved from the field on services quality and performance level. The service quality (SERVQUAL) model (a multi-dimensional research instrument designed to capture consumer expectations and perceptions of service) was modified thereby generating six dimensions and thirty-six service criteria for this research. The FAHP method was employed to determine the weights of the decision criteria because there is a need to measure commuters’ perceptions and expectations based on numerical linguistic variables due to the vague, imprecise and complexity related to the nature of services. The criteria weights and responses of the survey analysis (data) related with the BRT are input for the VIKOR method for ranking. As measuring the perception of service quality based on crispy value can often be misleading, hence, the use of the fuzzy MCDM method can give a more realistic measurement. The result of the multi-criteria decision analysis revealed that pricing quality is the most relevant service quality dimension to users’ satisfaction, followed by the empathy quality dimension. The summary of strength and weakness areas of service quality discovered through the research and its managerial implications with recommendations were related to the appropriate authority in charge of the BRT system for improved performance.

show abstract

Section: Vikor Methodsmentioning

confidence: 99%

Optimizing Service Quality Management of the Bus Rapid Transport System in Lagos Using the Multi-Criteria Decision Analysis

ADEBIYI¹,

AKINRINMADE²,

AMOLE³

2022

SJSUT.ST

View full text Add to dashboard Cite

show abstract

“…VIKOR provides a compromise solution [ 48 ] and, in the literature, the VIKOR algorithm is highly preferred not only in operations research and decision-making problems [ 49 , 50 ] but also in big data, information technology, and knowledge management fields. There are many different VIKOR applications and solutions regarding big data, such as selection criteria of the big data analysts [ 51 ], big data management in healthcare [ 52 ], big data solutions for dairy supply chains [ 53 ], augmented reality [ 53 ], mining big data [ 54 ], and so on.…”

Section: Smart Data Placementmentioning

confidence: 99%

Smart Data Placement Using Storage-as-a-Service Model for Big Data Pipelines

Khan

Nikolov

Matskin

et al. 2023

Sensors

View full text Add to dashboard Cite

Big data pipelines are developed to process data characterized by one or more of the three big data features, commonly known as the three Vs (volume, velocity, and variety), through a series of steps (e.g., extract, transform, and move), making the ground work for the use of advanced analytics and ML/AI techniques. Computing continuum (i.e., cloud/fog/edge) allows access to virtually infinite amount of resources, where data pipelines could be executed at scale; however, the implementation of data pipelines on the continuum is a complex task that needs to take computing resources, data transmission channels, triggers, data transfer methods, integration of message queues, etc., into account. The task becomes even more challenging when data storage is considered as part of the data pipelines. Local storage is expensive, hard to maintain, and comes with several challenges (e.g., data availability, data security, and backup). The use of cloud storage, i.e., storage-as-a-service (StaaS), instead of local storage has the potential of providing more flexibility in terms of scalability, fault tolerance, and availability. In this article, we propose a generic approach to integrate StaaS with data pipelines, i.e., computation on an on-premise server or on a specific cloud, but integration with StaaS, and develop a ranking method for available storage options based on five key parameters: cost, proximity, network performance, server-side encryption, and user weights/preferences. The evaluation carried out demonstrates the effectiveness of the proposed approach in terms of data transfer performance, utility of the individual parameters, and feasibility of dynamic selection of a storage option based on four primary user scenarios.

show abstract

“…Further, the separation measures which comprises of the maximum group utility values ( ) and the minimum individual regret values of the opponent design alternatives ( ) can also be obtained from equations 17 and 18 respectively [46,47]. The performance index VIKOR ( ) is also obtained in terms of fuzzy number from the minimum and maximum values of the group utility and individual regret of the opponent design alternative as presented in equation 19 [48][49][50].…”

Section: Fuzzy Vikormentioning

confidence: 99%

Fusing Multi-Attribute Decision Models for Decision Making to Achieve Optimal Product Design

Olabanji

Mpofu

2020

Foundations of Computing and Decision Sciences

View full text Add to dashboard Cite

Manufacturers need to select the best design from alternative design concepts in order to meet up with the demand of customers and have a larger share of the competitive market that is flooded with multifarious designs. Evaluation of conceptual design alternatives can be modelled as a Multi-Criteria Decision Making (MCDM) process because it includes conflicting design features with different sub features. Hybridization of Multi Attribute Decision Making (MADM) models has been applied in various field of management, science and engineering in order to have a robust decision-making process but the extension of these hybridized MADM models to decision making in engineering design still requires attention. In this article, an integrated MADM model comprising of Fuzzy Analytic Hierarchy Process (FAHP), Fuzzy Pugh Matrix and Fuzzy VIKOR was developed and applied to evaluate conceptual designs of liquid spraying machine. The fuzzy AHP was used to determine weights of the design features and sub features by virtue of its fuzzified comparison matrix and synthetic extent evaluation. The fuzzy Pugh matrix provides a methodical structure for determining performance using all the design alternatives as basis and obtaining aggregates for the designs using the weights of the sub features. The fuzzy VIKOR generates the decision matrix from the aggregates of the fuzzified Pugh matrices and determine the best design concept from the defuzzified performance index. At the end, the optimal design concept is determined for the liquid spraying machine.

show abstract

Fuzzy VIKOR approach for selection of big data analyst in procurement management

Cited by 16 publications

References 22 publications

Optimizing Service Quality Management of the Bus Rapid Transport System in Lagos Using the Multi-Criteria Decision Analysis

Optimizing Service Quality Management of the Bus Rapid Transport System in Lagos Using the Multi-Criteria Decision Analysis

Smart Data Placement Using Storage-as-a-Service Model for Big Data Pipelines

Fusing Multi-Attribute Decision Models for Decision Making to Achieve Optimal Product Design

Contact Info

Product

Resources

About