Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Wireless Networks
Published in: Wireless Networks 7/2016

01-10-2016

An empirical study on green practices of mobile phone users

Authors: Iosif Androulidakis, Vitaly Levashenko, Elena Zaitseva

Published in: Wireless Networks | Issue 7/2016

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Given the market’s saturation with smartphones and the increased power needs that these have as compared with older feature phones, the users’ green practices and behavior is emerging as an important research topic. The environmental aspects and general awareness issues are not addressed in this study; however, the limited battery life of smartphones is a decisive factor that shapes the users’ behavior, practices and preferences. As such, the users need to follow green practices and carefully assess the energy related characteristics (speed, screen size, weight, and price) that they value the most in a smartphone, to maximize their experience. Based on our previous work that gathered relevant data from 313 users, we extended the analysis in order to examine the user battery life and charging practices, buying habits, green practices and preferences. To that end, we used quantitative statistics and Fuzzy Decision Tree analysis to propose relevant Fuzzy Decision Rules that can classify the results and profile the users.
previous article An adaptive and efficient buffer management scheme for resource-constrained delay tolerant networks
next article Pascal’s triangle-based range-free localization for anisotropic wireless networks

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
2.
Androulidakis, I., Levashenko, V., & Zaitseva, E. (2014). Smart phone users: Are they green users? Proceedings of 10th international conference in digital technologies, Zilina, Slovakia, 1–6.
3.
Levashenko, V., & Zaitseva, E. (2002). Usage of new information estimations for induction of Fuzzy Decision Trees. In H. Yin, et al. (Eds.), Intelligent data engineering and automated learning–IDEAL 2002, Lecture notes in computer science (LNCS 2412) (pp. 493–499). Berlin Heidelberg New York: Springer.CrossRef
4.
Levashenko, V., Zaitseva, E., & Puuronen, S. (2007). Fuzzy classified based on Fuzzy Decision Tree. In Proceedings of the international conference on computer as a tool (EUROCON) (pp. 823–827), Warsaw, Poland.
5.
6.
Mitra, S., Konwar, K. M., & Pal, S. K. (2002). Fuzzy decision tree, linguistic rules and fuzzy knowledge-based network: Generation and evaluation. Journal of IEEE Transactions on Systems Man Cybernetics, Part C: Applications and Reviews, 32, 328–339.CrossRef
7.
8.
Crockett, K., Bandar, Z., & O’Shea, J. (2009). Fuzzification of discrete attributes from financial data in fuzzy classification trees. In Proceedings of IEEE international conference on fuzzy systems (pp. 1320–1325), Jeju Island, Korea.
9.
Levashenko, V., & Zaitseva, E. (2012). Fuzzy decision trees in medical decision making support system. In Proceedings of the IEEE federated conference on computer science & information systems (pp. 213–219), Wrocław, Poland.
10.
Stankevich, S., Levashenko, V., & Zaitseva, E. (2012). Fuzzy decision tree model adaptation to multi- and hyperspectral imagery supervised classification. In Proceedings of the 9th international conference on digital technologies (pp. 198–202), Zilina, Slovakia.
11.
Androulidakis, I., Pylarinos, D., & Kandus, G. (2012). Ciphering indicator approaches and user awareness, Maejo Int. Journal of Science and Technology, 6(03), 514–527.
12.
Androulidakis, I., & Kandus, G. (2013). Mobile phone security—Awareness and practices. Journal of the Institute of Telecommunications Professionals, 7(1), 16–23.
13.
Ansari, N.L., Ashraf, M.M., Malik, B.T., & Grunfeld, H. (2010). Green IT awareness and practices: Results from a field study on mobile phone related e-waste in Bangladesh. In Proceedings of the IEEE international symposium on technology and society (ISTAS) (pp. 375–383).
14.
15.
Burns, J. C., Kassam, Adil, Sinha, N. N., Downie, L. E., Solnickova, L., Way, B. M., & Dahn, J. R. (2013). Predicting and extending the lifetime of Li-ion batteries. Journal of the Electrochemical Society, 160, A1451–A1456.CrossRef
16.
IEC 62684 ed.1.0 Interoperability specifications of common external power supply (EPS) for use with data-enabled mobile telephones, January 2011.
17.
Carroll, A., & Heiser, G. (2010). An analysis of power consumption in a smartphone. In Proceedings of the 2010 USENIX annual technical conference (pp. 271–284).
18.
Carroll, A., & Heiser, G. (2013). The systems hacker’s guide to the galaxy energy usage in a modern smartphone. In Proceedings of the 4th Asia-Pacific workshop on systems, Article No. 5.
19.
20.
Huang, J., Qian, F., Gerber, A., Morley Mao, Z., Sen, S, & Spatscheck, O. (2012). A close examination of performance and power characteristics of 4G LTE Networks. In Proceedings of the 10th international conference on mobile systems, applications and services (pp. 225–238), Lake District, United Kingdom.
21.
22.
Jiang, D., Xu, Z., Liu, J., & Zhao, W. (2015). An optimization-based robust routing algorithm to energy-efficient networks for cloud computing. Telecommunication Systems. doi:10.​1007/​s11235-015-9975-y.
23.
Jiang, D., Xu, Z., Li, W., & Chen, Z. (2014). Topology control-based collaborative multicast routing algorithm with minimum energy consumption. International Journal of Communication Systems,. doi:10.​1002/​dac.​2905.
24.
Dillman, D. A. (1999). Mail and internet surveys: The tailored design method (2nd ed.). New York: Wiley.
25.
Pfleeger, S. L., & Kitchenham, B. A. (2001). Principles of survey research. Part 1: Turning lemons into lemonade. ACM SIGSOFT Software Engineering Notes, 26(6), 16–18.CrossRef
26.
Androulidakis, I., & Kandus, G. (2010). Trends in users’ security perceptions regarding mobile phone usage. In Proceedings of 14th WSEAS international conference on communications (pp. 63–69).
27.
28.
The Global mobile Suppliers Association. (2014). Mobile HD voice: Global update report. www.​gsacom.​com. Accessed March, 2014.
Metadata
Title
An empirical study on green practices of mobile phone users
Authors
Iosif Androulidakis
Vitaly Levashenko
Elena Zaitseva
Publication date
01-10-2016
Publisher
Springer US
Published in
Wireless Networks / Issue 7/2016
Print ISSN: 1022-0038
Electronic ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-015-1097-7

Other articles of this Issue 7/2016

Wireless Networks 7/2016 Go to the issue

OriginalPaper

Multipath routing in mobile ad hoc network with probabilistic splitting of traffic

OriginalPaper

Joint scheduling and routing using space–time graphs for TDM wireless mesh networks

OriginalPaper

E2EACK: an end-to-end acknowledgment-based scheme against collusion black hole and slander attacks in MANETs

OriginalPaper

Applying trust enhancements to reactive routing protocols in mobile ad hoc networks

OriginalPaper

On the performance of cooperative cognitive networks with proactive relay selection

OriginalPaper

Truthful budget constrained auction for device-to-device relaying packet allocation