Mobile Applications Usability Parameters: Taking an Insight View

Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 9)


Nowadays, mobiles are like the general purpose computers with inbuilt sensors, constant access to Internet and a huge variety of applications. Different applications are categorized in such a way that they can perform their task in the best possible manner. Usability of mobile applications is the ability of an individual to use the application for its intended purpose without getting frustrated. In this paper, the attention draws on the major usability factors of different applications. After finding out the factors, we are trying to give the brief introduction of various methodologies used to rank the factors and the structural relationships among these parameters are modeled. Major techniques among them are interpretive structural modeling (ISM) approach, analytical hierarchal approach (AHP) and DEMETAL (decision-making trial and evaluation technique). These methodologies are used to identify parameters affecting mobile applications, and the structural relationships between these parameters are modeled.


Usability Mobile applications Parameters ISM DEMATAL AHP TOPSIS 


  1. 1.
    Hardy R, Rukzio E (2009) Exploring expressive NFC-based mobile phone interaction with large dynamic displays. In: First international workshop on near field communicationGoogle Scholar
  2. 2.
    Brodt A (2012) A mobile data management architecture for interoperability of resource and context data. In: 12th IEEE (international conference on mobile data managementGoogle Scholar
  3. 3.
    Forman G, Zahorjan J (1994) The challenges of mobile computing. IEEE ComputGoogle Scholar
  4. 4.
    Hazarika P (2014) Recommendations for webview based mobile applications on android. In: IEEE international conference on advanced communication control and computing technologies (ICACCCT)Google Scholar
  5. 5.
    Constantinos K (2012) Coursaris: a meta-analytical review of empirical mobile usability studies. JUS J 6(3):117–171Google Scholar
  6. 6.
    Definition of mobile applications.
  7. 7.
    Kwahka J, Han SH (2002) A methodology for evaluating the usability of audiovisual consumer electronic products. Elsevier scienceGoogle Scholar
  8. 8.
    Bevan N, Curson I Methods for measuring usabilityGoogle Scholar
  9. 9.
    Harrison R, Flood D, Duce D (2013) Usability of mobile applications: literature review an d rationale for a new usability model. J Interact SciGoogle Scholar
  10. 10.
    Saleh A, Isamil RB, Fabil NB (2015) Extension of PACMAD model for usability evaluation metrics using goal question metrics (gqm) approach. J Theor Appl Inf Technol 79(1):1992–8645Google Scholar
  11. 11.
    Patel N, Dalal P (2013) Usability evaluation of mobile applications. Int J Eng Res Technol (IJERT) 2(11):2278–018Google Scholar
  12. 12.
    Saleh AM, Ismail RB Usability evaluation frameworks of mobile application: a mini-systematic literature reviewGoogle Scholar
  13. 13.
  14. 14.
    Nayebi F, Desharnais JM, Abran A The state of the art of mobile application usability evaluationGoogle Scholar
  15. 15.
    Coursaris CK, Kim DJ (2011) A meta-analytical review of empirical mobile usability studies. J Usability Stud 6(3):117–171Google Scholar
  16. 16.
    Xu L, Yang JB (2011) Introduction to multi-criteria decision making and the evidential reasoning approachGoogle Scholar
  17. 17.
    Gavade RK (2012) Multi-criteria decision making: an overview of different selection problems and methods: (IJCSIT). Int J Comput Sci Inf Technol 5(4):5643–5646Google Scholar
  18. 18.
    Triantaphyllou E, Shu B, Sanchez SN, Ray T (1998) Multi-criteria decision making: an operations research approach. In: Webster JG (ed) Encyclopedia of electrical and electronics engineering, vol 15. Wiley, New York, NY, pp 175–186Google Scholar
  19. 19.
    Arabameri A (2014) Application of the analytic hierarchy process (AHP) for locating fire stations: case study Maku city. Merit Res J Art, Soc Sci Humanit 2(1):001–010, ISSN 2350–2258Google Scholar
  20. 20.
    Abu-Sarhan Z (2011) Application of analytic hierarchy process (AHP) in the evaluation and selection of an information system reengineering projects. IJCSNS Int J Comput Sci Netw Secur 11(1)Google Scholar
  21. 21.
    Saaty TL (2008) Decision making with the analytic hierarchy process: Int J Serv Sci 1(1)Google Scholar
  22. 22.
    Definition of multi attribute utility theory.
  23. 23.
  24. 24.
    Guerrero-Baena MD, Gómez-Limón JA, Fruet Cardozo JV Are multi-criteria decision making techniques useful for solving corporate finance problems? pp 60–79Google Scholar
  25. 25.
    Kabassi K, Virvou M (2014) Multi-attribute utility theory and adaptive techniques for intelligent web-based educational software: Instr Sci 34(2):313–158Google Scholar
  26. 26.
    Sushil Interpreting the interpretive structural model. Global J Flex Syst Manage 0972–2696Google Scholar
  27. 27.
    George JP, Pramod VR (2014) An interpretive structural model (ISM) analysis approach in steel rerolling mills (SRRMs). IMPACT: Int J Res Eng Technol (IMPACT: IJRET) 2:161–174, ISSN 2321–8843Google Scholar
  28. 28.
    Jayalakshmi B (2014) Interpretive structural modeling of the inhibitors of wireless control system in industry. In: International conference on industrial engineering and operations management, Bali, Indonesia, January 7–9Google Scholar
  29. 29.
    Panda BN, Biswal BB, Deepak BBLV (2014) Integrated AHP and fuzzy TOPSIS approach for the selection of a rapid prototyping process under multi-criteria perspective. In: 5th international & 26th all india manufacturing technology, design and research conference (AIMTDR 2014) IIT Guwahati, Assam, India, December (2014)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Amity School of Engineering and TechnologyAmity UniversityNoidaIndia

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