EconPapers    
Economics at your fingertips  
 

Survey for Sensor-Cloud System from Business Process Outsourcing Perspective

JeongYeon Kim
Additional contact information
JeongYeon Kim: Sangmyung University, 20, Hongjimun 2-gil, Jongno-gu, Seoul 110-743, Republic of Korea

International Journal of Distributed Sensor Networks, 2015, vol. 11, issue 9, 917028

Abstract: Cloud computing is a new IT trend to meet the new business requirements such as business agility and operational efficiency with business process outsourcing (BPO). Sensor-Cloud infrastructure is the extended form of cloud computing to manage the sensors which are scattered throughout the network. Several benefits of adopting cloud computing including cost saving, high scalability, and business risk reductions also can be applied to sensor data collection. As a first investment for new technology, we analyze IT managers' feedbacks to identify the most important factors of decision making for cloud platform adoption and IT outsourcing. Even though the technological motivation is persuasive in Korean IT market, survey results show that the cost efficiency is the most important for cloud platform adoption. Also surveys reveal that IT service consumers have difficulties understanding complicated service contracts and data sharing issues with infrastructure providers, which serve as main blockers of adopting cloud computing.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1155/2015/917028 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:11:y:2015:i:9:p:917028

DOI: 10.1155/2015/917028

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().

 
Page updated 2025-03-19
Handle: RePEc:sae:intdis:v:11:y:2015:i:9:p:917028