Improving the Cosine Consistency Index for the analytic hierarchy process for solving multi-criteria decision making problems

Khatwani, Gaurav; Kar, Arpan Kumar

doi:10.1016/j.aci.2016.05.001

Cited by 40 publications

(19 citation statements)

References 86 publications

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“…The decision maker's judgment is crisp value which describes the relationship between paired comparisons. Among similar approaches, there are over 20 approaches for prioritization of preferences or judgments [30], however very few of these recent approaches have been used for empirical case studies.…”

Section: Methodsmentioning

confidence: 99%

Evaluating Multi-dimensional Risk for Digital Services in Smart Cities

Mustafa

Kar

2017

Digital Nations – Smart Cities, Innovation, and Sustainability

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In current times, emerging economies are providing digital services to its citizen through public or private organization. Literature indicates that digital services are facing major challenges with respect to its adoption among relevant users groups, largely due to the perceived risks surrounding digital services. A purposive sampling methodology was adopted for the empirical validation of the framework among user groups. With the use of Generalized Analytic Network Process (GANP), prioritization of different dimensions of risk has been illustrated. The result indicates that dimensions like privacy risk, performance risk and financial risk are the most important risk across digital services models. However physical risk, social risk, psychological risk and time risk are comparatively less important risk across digital services. This research also finds out that the end users are reluctant to provide their personal information. The sample size is relatively small which limits generalizability of results. However an application of GANP has been showcased for empirical research. The research outcome can help managers in deciding which dimensions of risk are more important for digital service delivery. This study focuses on the different facets of risk perceived by consumers towards the digital services available in smart cities. Perceived risk dimensions like privacy risk, performance risk, financial risk, physical risk, social risk, psychological risk and time risk, have shown that there is a need to prioritize these risk to the digital services which is offered to the residents of the smart cities.

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Section: Methodsmentioning

confidence: 99%

Evaluating Multi-dimensional Risk for Digital Services in Smart Cities

Mustafa

Kar

2017

Digital Nations – Smart Cities, Innovation, and Sustainability

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“…The analytic hierarchy process (AHP), developed by Thomas Saaty [9], is an effective method for dealing with complex decision-making from the elicited judgments from experts [10]. This method helps decision-makers set priorities between alternatives, sub-criteria and criteria in the decision-making process and also helps them to make the best decision [11][12][13][14][15][16][17].…”

Section: Methodsmentioning

confidence: 99%

The Selection of Anchoring System for Floating Houses by Means of AHP Method

2020

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This paper indicates and analyses the use of anchoring systems, such as mooring piles, booms, mooring cables, and deadweight anchors with additional elastic connectors, which are the most frequently applied by the producers of floating houses. The selection of the most advantageous anchoring system is complicated and requires the application of quantitative and qualitative data and methods. This publication presents the results of the calculations using one of the most common methods of multi-criteria analysis of decision-making, namely AHP (analytic hierarchy process). The anchoring system, which is the most beneficial for users, has been indicated with the use of the main criteria such as: cost, time, external risk factors, geospatial factors, and the sub-criteria of the first and second order. Due to the conducted analysis, it has been shown that the most significant factor of the anchoring system selection for the users of floating houses is the investment cost that needs to be borne during the usage, and the most favourable anchoring system is the use of mooring cables.

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“…Prioritization of risk involves the multiple conflicting criteria with finite set of alternatives (Wang et al, 2009). Different MCDM technique such as analytic hierarchy process (AHP) (Khatwani and Kar, 2017;Zeshui and Cuiping, 1999), analytic network process (ANP) (Jharkharia and Shankar, 2007;Cheng et al, 2005), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) (Kumar and Dash, 2017;Kermani et al, 2016), ELimination and Choice Expressing REality (ELECTRE) (Shojaie et al, 2018;Ergazakis et al, 2011), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) (Senthil et al, 2018;Mardani et al, 2015) and VIKOR (Wan et al, 2013;Mardani et al, 2015) has been applied in prioritization problems.…”

Section: Methodsmentioning

confidence: 99%

When the mobile app is free, the product is your personal data

Polykalas

Prezerakos

2019

DPRG

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Purpose-Mobile devices (smartphones, tables etc.) have become the de facto means of accessing the internet. While traditional Web browsing is still quite popular, significant interaction takes place via native mobile apps that can be downloaded either freely or at a cost. This has opened the door to a number of issues related to privacy protection since the smartphone stores and processes personal data. The purpose of this paper is to examine the extent of access to personal data, required by the most popular mobile apps available in Google Play store. In addition, it is examined whether the relevant procedure is in accordance with the provisions of the new EU Regulation. Design/methodology/approach-The paper examines more than a thousand mobile apps, available from the Google Play store, with respect to the extent of the requests for access to personal data. In particular, for each available category in Google Play store, the most popular mobile apps have been examined both for free and paid apps. In addition, the permissions required by free and paid mobile apps are compared. Furthermore, a correlation analysis is carried out aiming to reveal any correlation between the extent of required access to personal data and the popularity and the rating of each mobile app. Findings-The findings of this paper suggest that the majority of examined mobile apps require access to personal data to a high extent. In addition, it is found that free mobile apps request access to personal data in a higher extent compared to the relevant requests by paid apps, which indicates strongly that the business model of free mobile apps is based on personal data exploitation. The most popular types of access permissions are revealed for both free and paid apps. In addition, important questions are raised in relation to user awareness and behavior, data minimization and purpose limitation for free and paid mobile apps. Originality/value-In this study, the process and the extent of access to personal data through mobile apps are analyzed. Although several studies analyzed relevant issues in the past, the originality of this research is mainly based on the following facts: first, this work took into account the recent Regulation of the EU in relation to personal data (GDPR); second, the authors analyzed a high number of the most popular mobile apps (more than a thousand); and third, the authors compare and analyze the different approaches followed between free and paid mobile apps.

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Improving the Cosine Consistency Index for the analytic hierarchy process for solving multi-criteria decision making problems

Cited by 40 publications

References 86 publications

Evaluating Multi-dimensional Risk for Digital Services in Smart Cities

Evaluating Multi-dimensional Risk for Digital Services in Smart Cities

The Selection of Anchoring System for Floating Houses by Means of AHP Method

When the mobile app is free, the product is your personal data

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