A competitive hedonic consumption estimation for IoT service distribution

Deepsubhra Guha Roy; Bipasha Mahato; Debashis De

doi:10.23919/URSIAP-RASC.2019.8738626

A competitive hedonic consumption estimation for IoT service distribution

Deepsubhra Guha Roy, Bipasha Mahato, Debashis De

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

5 Citations (Scopus)

Abstract

Cost estimation of IoT service subscription is directly associated with the quality of experience, upload/ download speed of a subscription link. This article consider a dynamic Adaptive Bit Rate (ABR) streaming based wireless communication service to estimate hedonic consumption of bandwidth distribution for IoT service subscription. Hedonic price model has exploited jointly with Semi-Log estimation and Lagrange multiplier tests. Judgment of the total estimation has concluded that the value of internet information is totally dependent upon the user- willingness to pay and elasticity of individual service variable. Based on the result of hedonic price estimation it has established that ISPs can charge on the basis of IoT service usage over wireless connectivity, instead of offering all the services at fixed cost.

Original language	English
Title of host publication	2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019
Publisher	IEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9789082598759
DOIs	https://doi.org/10.23919/URSIAP-RASC.2019.8738626
Publication status	Published - 1 Mar 2019
Event	2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019 - New Delhi, India Duration: 9 Mar 2019 → 15 Mar 2019

Publication series

Name	2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019

Conference

Conference	2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019
Country/Territory	India
City	New Delhi
Period	9/03/19 → 15/03/19

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10.23919/URSIAP-RASC.2019.8738626

Cite this

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title = "A competitive hedonic consumption estimation for IoT service distribution",

abstract = "Cost estimation of IoT service subscription is directly associated with the quality of experience, upload/ download speed of a subscription link. This article consider a dynamic Adaptive Bit Rate (ABR) streaming based wireless communication service to estimate hedonic consumption of bandwidth distribution for IoT service subscription. Hedonic price model has exploited jointly with Semi-Log estimation and Lagrange multiplier tests. Judgment of the total estimation has concluded that the value of internet information is totally dependent upon the user- willingness to pay and elasticity of individual service variable. Based on the result of hedonic price estimation it has established that ISPs can charge on the basis of IoT service usage over wireless connectivity, instead of offering all the services at fixed cost.",

author = "Roy, {Deepsubhra Guha} and Bipasha Mahato and Debashis De",

year = "2019",

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language = "English",

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note = "2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019 ; Conference date: 09-03-2019 Through 15-03-2019",

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Roy, DG, Mahato, B & De, D 2019, A competitive hedonic consumption estimation for IoT service distribution. in 2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019., 8738626, 2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019, IEEE, Institute of Electrical and Electronics Engineers, 2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019, New Delhi, India, 9/03/19. https://doi.org/10.23919/URSIAP-RASC.2019.8738626

A competitive hedonic consumption estimation for IoT service distribution. / Roy, Deepsubhra Guha; Mahato, Bipasha; De, Debashis.
2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019. IEEE, Institute of Electrical and Electronics Engineers, 2019. 8738626 (2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019).

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

TY - GEN

T1 - A competitive hedonic consumption estimation for IoT service distribution

AU - Roy, Deepsubhra Guha

AU - Mahato, Bipasha

AU - De, Debashis

PY - 2019/3/1

Y1 - 2019/3/1

N2 - Cost estimation of IoT service subscription is directly associated with the quality of experience, upload/ download speed of a subscription link. This article consider a dynamic Adaptive Bit Rate (ABR) streaming based wireless communication service to estimate hedonic consumption of bandwidth distribution for IoT service subscription. Hedonic price model has exploited jointly with Semi-Log estimation and Lagrange multiplier tests. Judgment of the total estimation has concluded that the value of internet information is totally dependent upon the user- willingness to pay and elasticity of individual service variable. Based on the result of hedonic price estimation it has established that ISPs can charge on the basis of IoT service usage over wireless connectivity, instead of offering all the services at fixed cost.

AB - Cost estimation of IoT service subscription is directly associated with the quality of experience, upload/ download speed of a subscription link. This article consider a dynamic Adaptive Bit Rate (ABR) streaming based wireless communication service to estimate hedonic consumption of bandwidth distribution for IoT service subscription. Hedonic price model has exploited jointly with Semi-Log estimation and Lagrange multiplier tests. Judgment of the total estimation has concluded that the value of internet information is totally dependent upon the user- willingness to pay and elasticity of individual service variable. Based on the result of hedonic price estimation it has established that ISPs can charge on the basis of IoT service usage over wireless connectivity, instead of offering all the services at fixed cost.

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M3 - Conference paper

T3 - 2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019

BT - 2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - 2019 URSI Asia-Pacific Radio Science Conference, AP-RASC 2019

Y2 - 9 March 2019 through 15 March 2019

ER -

A competitive hedonic consumption estimation for IoT service distribution

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