LRAP: Layered Ring Based Adaptive and Personalized Usability Model for Mobile Commerce Apps

Authors

DOI:

https://doi.org/10.3991/ijim.v17i12.37995

Keywords:

Usability model, m-commerce, mobile apps, online shopping

Abstract


Usability is one of the most important characteristics of software applications, especially when it comes to mobile shopping applications. There is a great deal of shift from traditional shopping to online shopping because it benefits both parties i.e., customers as well as businessmen. In such a scenario, the usability factor can play a very vital role in the business industry. If a client stops using a mobile shopping app because it is not user-friendly, it can badly damage the annual revenues especially when hundreds of alternatives are available and there is tough competition. Therefore, to keep existing customers intact and to attract new customers, it is very important to provide a user-friendly mobile app to customers. In this paper, we consider a large variety of online customers with diverse requirements. background and constraints and evaluate the usability of existing mobile e-commerce apps to identify the actual problems people are facing with existing applications and do a systematic review of existing shopping apps. Then, we propose a personalized and adaptive usability model for mobile commerce apps considering the neglected user type i.e., illiterates and people with tactile disabilities. The proposed model LRAP is a layered approach from generalization to specification and it can be considered an extension of the famous PACMAD usability model. Besides this, we also suggest a combining score tool which will be helpful in measuring the usability of any app.

Author Biographies

Malik Muhammad Saad Missen, Dept. of IT, The Islamia University of Bahawalpur.

Dr. Malik Muhammad Saad Missen is working as an Associate Professor in the IT department of the Islamia University of Bahawalpur. His major fields of interest are Text Mining, Usability Engineering, and Document Image Analysis. He completed his Ph.D. in 2011 and Post Doc in 2015 from France. He has supervised more than 6 Ph.D. students and 60 Master's students.

Surya Prasath, University of Cincinnati

Surya Prasath, PhD, is a mathematician with two decades of experience in the research areas of image processing, computer vision and machine learning. He received his MSc, and PhD in mathematics from the Indian Institute of Technology Madras, India in 2004 and 2009. He was a Postdoctoral Fellow at the Department of Mathematics, University of Coimbra, Portugal from 2010 to 2011. From 2012 to 2015 he was with the Computational Imaging and VisAnalysis (CIVA) Lab at the University of Missouri, USA as a Postdoctoral Fellow, and from 2016 to 2017 as an Assistant Professor. He is currently an Assistant Professor in the Division of Biomedical Informatics at the Cincinnati Children's Hospital Medical Center, and Departments of Biomedical Informatics, Pediatrics, Electrical Engineering, and Computer Science, at the University of Cincinnati from 2018

Cover iJIM Vol. 17 No. 12 (2023)

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Published

2023-06-20

How to Cite

Ul Ain, Q., Missen, M. M. S., & Prasath, S. (2023). LRAP: Layered Ring Based Adaptive and Personalized Usability Model for Mobile Commerce Apps. International Journal of Interactive Mobile Technologies (iJIM), 17(12), pp. 74–93. https://doi.org/10.3991/ijim.v17i12.37995

Issue

Vol. 17 No. 12 (2023)

Section

Papers

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Copyright (c) 2023 Qurat Ul Ain, Malik Muhammad Saad Missen, Surya Prasath

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