A Grey Model for Evaluation of Information Systems Security

Shi, Huawang; Deng, Yong

doi:10.4304/jcp.7.1.284-291

Cited by 12 publications

(6 citation statements)

References 3 publications

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“…Bu durumda birleştirilmiş matris muhtemelen tutarlı çıkacaktır. (Aksoy, Ömürbek, & Karaatlı, 2015) E-kitap okuyucu seçimi (Özen & Orcanlı, 2013) Tedarikçi seçimi (Supçiller & Çapraz, 2011;Shaw, Shankar, Yadav, & Thakur, 2012) Tomografi cihazı seçimi (Barrios , ve diğerleri, 2016) Hava aracı seçimi (Dožić & Kalić, 2014;Dožić & Kalić, 2015) Futbolcu performanslarının değerlendirilmesi (Karaatlı , Ömürbek, & Köse , 2014) Arama ve kurtarma aracı seçimi (Şahin & Akyer , 2011) E-işletmelerde hizmet kalitesinin değerlendirilmesi (Lee & Kozar, 2006;Chou & Cheng, 2012;Ustasüleyman, 2013) Satın alma kararlarını etkileyen faktörlerin değerlendirilmesi (Atalık & Özdemir, 2014) Bilişim sistemleri risk değerlendirme (Shi & Deng, 2012) Tablo 3. ise . kriterin optimal değerini göstermektedir.…”

Section: = (37)unclassified

An Integrated Approach to the Evaluation of E-Service Quality in Airline Companies [Havayolu İşletmeleri̇nde E-Hi̇zmet Kali̇tesi̇ni̇n Değerlendi̇ri̇lmesi̇ne Yöneli̇k Bütünleşik Bir Yaklaşım]

Bakır¹

2019

Preprint

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Nowadays, as a result of technological developments, information technology has deeply affected the activities of many sectors and has begun to support these sectors as amarketing tool. The air transport sector is undoubtedly one of these sectors. It is known that ticket sales are largely carried out over the internet in the air transport industry where passengers are basically transported from one place to another. In this point as well as in other services, the concept of quality (e-service) also stands out as an important competition tool in the services offered over the internet. As a matter of fact, e-service quality affects customer satisfaction and loyalty positively, which is decisive on the success of airline companies. In this context, it is aimed to determine the importance levels of the factors affecting the quality of e-services offered in the air transport sector by using integrated methods in the study and to rank the national airline companies according to their e-service quality performances. For this purpose, firstly, the factors affecting the quality of e-service were obtained as a result of the literature survey. A hierarchical model was established with the elements obtained and the importance of the factors affecting the quality of e-serviceas a result of expert opinions were determined using the Analytical Hierarchy Process (AHP). In the next phase of the study, the data obtained as a result of the questionnaire applied to 395 passengers at International Antalya Airport were analyzed using the ARAS method and ranked according to the performances of airlines. According to the results obtained; it has been determined that the most important factor that has an effect on e-service quality is reliability and Atlasglobal has the highest e-service quality performance.

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An Integrated Approach to the Evaluation of E-Service Quality in Airline Companies [Havayolu İşletmeleri̇nde E-Hi̇zmet Kali̇tesi̇ni̇n Değerlendi̇ri̇lmesi̇ne Yöneli̇k Bütünleşik Bir Yaklaşım]

Bakır¹

2019

Preprint

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“…23 This theory has been applied mostly to various types of non-engineering problems as well as some engineering applications. 24 The applications of the grey system theory include energy conversion and management, 25 system security, 26 earthquake forecasting 27 and medical diagnosis. 28 In the grey system theory, the uncertain parameters are assumed to be grey numbers, each with a lower and upper bound value, and are represented similar to those of interval numbers.…”

Section: Introductionmentioning

confidence: 99%

Interval-based uncertainty models for micromechanical properties of composite materials

Alazwari

Rao

2018

Journal of Reinforced Plastics and Composites

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Extensive work has been done in the past few decades to quantify the uncertainties associated with the micromechanics of composite materials in the presence of uncertainties in constituent material properties using probabilistic approaches. However, the probabilistic approaches require a knowledge of the probability distributions of the input parameters which are not known in most cases. This work presents interval-based uncertainty analysis using probabilistic approach with three sigma band about the mean, interval analysis method and the universal grey system (number) theory. Since the interval analysis predicts wider ranges and, in some cases, might violate the physical laws of the problem, the truncation-based interval analysis is presented to overcome the overestimation caused in the computed quantities by the so-called dependency problem associated with the interval analysis. The uncertainties exhibited in the micromechanics characteristics of composite materials due to the presence of uncertainties in the constituent material properties are investigated. The propagation of these uncertainties to the response characteristics of an angle-ply lamina is also studied. In the numerical study, two types of composite materials are considered – the graphite/epoxy and glass/epoxy systems – to demonstrate and compare the influence of the uncertainty models on the results. This work shows that improved and more meaningful results can be obtained using the universal grey system theory compared to the interval analysis, truncation-based interval analysis and probabilistic method for the micromechanics of composite materials and the response of an angle-ply lamina when the fiber and matrix properties are uncertain.

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“…GRA is an impact evaluation model that measures the degree of similarity or difference between two situations based on the grade of relation [13]. GRA contains four steps to generate the global comparison among the alternatives [14].…”

Section: Grey Relational Analysismentioning

confidence: 99%

“…In the middle, grey systems will give a variety of available solutions. The analysis does not attempt to find the best solution, but does provide techniques for determining a good solution, an appropriate solution for real world problems.GRA is an impact evaluation model that measures the degree of similarity or difference between two situations based on the grade of relation [13]. GRA contains four steps to generate the global comparison among the alternatives [14].…”

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confidence: 99%

Optimising Computer Laboratory Layout Based on Multiple Performance Measures

Judi¹,

Mohamed²

2016

IJIET

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Abstract-Awareness to select computer laboratory layout has been increased in recent years as more academic administration have come to realize its potential for contributing to conducive teaching and learning environment. Studies on physical design of computer laboratory including optimizing its layout to achieve comfort and fulfill its function are yet little. This paper proposes the optimization of computer laboratory layout using multiple performance measures. The use of grey relational analysis is presented to evaluate and select the best among the proposed four new layouts. The evaluation and selection were performed based on three performance parameters: capacity, total surface area and utility of space. The performance measures were considered to be of equal weight. The use of grey relational analysis shows reliable solution could be suggested that provide a better distinction among the given alternatives.Index Terms-Modeling, learning environment, grey relational analysis. I. INTRODUCTIONAcademic organizations are facing challenges in using their facilities to support main activities: teaching, learning and research. This issue is related to layout management i.e. the arrangement of tools, and usage of space to achieve comfort and fulfill the purpose [1]. Layout plays an important role in developing a conducive environment that supports learning. Among important facilities that require good layout planning is computer laboratory. Computer labs must be designed intelligently and serve the purpose they were intended to serve [2], [3]. Generally, there are two types of users in academic computer laboratory: students and instructors [4]. The needs and requirements of these users need to be identified to ensure this facility supports the purpose especially in current development of learning environment.The recent development of computer technology and availability has led to the rise of laptop and other computer ownership among students and eventually eliminated the need for campus computing laboratories [5], [6]. However, the continued need of computer laboratories in teaching and learning process is reasonable due to the need for standardized software and hardware configurations, high cost and complexity of many specialized software applications and limited number of software license to support educational Manuscript received December 23, 2014; revised April 10, 2015 activities [7].Awareness to select computer laboratory layout has been increased in recent years as more academic administration have come to realize its potential for contributing to conducive teaching and learning environment. Selecting the best arrangement may become crucial issue considering the number of students to occupy the room and hence the number of computers to cater the needs. For example, the frequency of student-to-student and student-to-teacher interactions indicated that the pod arrangement supported more collaboration than the straight row of laboratory arrangement [8].Usually, as many as 40 students register for a certain pr...

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A Grey Model for Evaluation of Information Systems Security

Cited by 12 publications

References 3 publications

An Integrated Approach to the Evaluation of E-Service Quality in Airline Companies [Havayolu İşletmeleri̇nde E-Hi̇zmet Kali̇tesi̇ni̇n Değerlendi̇ri̇lmesi̇ne Yöneli̇k Bütünleşik Bir Yaklaşım]

An Integrated Approach to the Evaluation of E-Service Quality in Airline Companies [Havayolu İşletmeleri̇nde E-Hi̇zmet Kali̇tesi̇ni̇n Değerlendi̇ri̇lmesi̇ne Yöneli̇k Bütünleşik Bir Yaklaşım]

Interval-based uncertainty models for micromechanical properties of composite materials

Optimising Computer Laboratory Layout Based on Multiple Performance Measures

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