• ISSN: 2148-2225 (online)

Ulaştırma ve Lojistik Kongreleri

alphanumeric journal

The Journal of Operations Research, Statistics, Econometrics and Management Information Systems

Examining the Factors Influential on Smart Phone Users' Satisfaction Levels: A Case Study from Eskisehir


Hatice Şamkar, Ph.D.


Abstract

Parallel to the rapid developments in technology, a rapid change has been experienced in communication tools as well. As a result, smart phones can now perform a number of computer procedures besides allowing ordinary telephone conversations. Today, it is seen that smart phone use is quite common especially among young people. The present study focuses on smart phone users’ levels of satisfaction with smart phones and on the factors likely to be influential on their satisfaction levels. For this purpose, the related research data were collected with a questionnaire conducted in Eskisehir, and factor analysis was carried out to determine the factors regarding the participants’ attitudes towards smart phone use. Lastly, with the help of logistic regression analysis, a mathematical model was developed to determine the smart phone users’ satisfaction levels.

Keywords: Factor Analysis, Logistic Regression Analysis, Smart Phone Users’ Satisfaction Levels

Jel Classification: C38, C44

Akıllı Telefon Kullanıcılarının Memnuniyet Düzeylerinde Etkili Olan Faktörlerin İncelenmesi: Eskişehir Örneği


Öz

Teknolojinin hızlı gelişimiyle birlikte iletişim araçlarında da hızlı bir değişim yaşanmış ve sıradan telefon görüşmelerinin yanı sıra pek çok bilgisayar işlemini de gerçekleştirebilen akıllı telefonlar günlük yaşantımızda yerini almıştır. Günümüzde özellikle gençler arasında akıllı telefon kullanımının oldukça yaygın olduğu gözlenmektedir. Akıllı telefon kullanıcılarının, akıllı telefon kullanımına ilişkin memnuniyet düzeyleri ve bunda etkili olabilecek faktörler bu çalışmanın amacını oluşturmaktadır. Bunun için Eskişehir kapsamında yürütülen bir anket ile toplanan verilere faktör analizi uygulanarak akıllı telefon kullanımıyla ilgili tutumlardan akıllı telefon kullanımına ilişkin faktörler tespit edilmeye çalışılmıştır. Daha sonra lojistik regresyon analizi yardımıyla akıllı telefon kullanıcılarının memnuniyet derecelerini belirleyen matematiksel bir model kurulmuştur.

Anahtar Kelimeler: Akıllı Telefon Kullanımına İlişkin Memnuniyet Düzeyi, Faktör Analizi, Lojistik Regresyon Analizi


Cite this article

Şamkar, H. (2017). Examining the Factors Influential on Smart Phone Users' Satisfaction Levels: A Case Study from Eskisehir. Alphanumeric Journal, 5(1), 147-162. http://dx.doi.org/10.17093/alphanumeric.323829

References

  • Ada S. and Tatlı H.S. (2013). Akıllı Telefon Kullanımını Etkileyen Faktörler Üzerine Bir Araştırma. Paper Presented at Akademik Bilişim 2013 Conference. Akdeniz University. Turkey. (Retrieved January 18, 2016, from http://ab.org.tr/ab13/bildiri/74.pdf)
  • Armstrong N., Nugent C., Moore G. and Finlay D. (2010). Using Smartphones to Adres the Needs of Persons with Alzheimer’s Disease. Annals Telecomunications, 65: 485-495.
  • Armstrong N., Nugent C., Moore G. and Finlay D. (2012). Inactivity Monitoring for People with Alzheimer’s Disease Using Smartphone Technology. Wireless Mobile Communication and Healthcare: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 83: 313-321.
  • Baumgart D. (2011). Smartphones in Clinical Practice, Medical Education, and Research. JAMA Internal Medicine, 171 (14): 1294-1296.
  • Bewick V., Cheek L. and Ball J. (2005). Statistics Review 14: Logistic Regression. Crit Care, 9(1): 112-118.
  • Brown T.A. (2006). Confirmatory Factor Analysis for Applied Research: London.
  • Carayannis E.G. and Clark S.C. (2011). Do Smartphones Make for Smarter Business? The Smartphone CEO Study. Journal of the Knowledge Economy, 2(2): 201-233.
  • Carayannis E.G., Clark S.C. and Valvi D.E. (2013). Smartphone Affordance: Achieving Better Business Through Innovation. Journal of the Knowledge Economy, 4(4): 444-472.
  • Chang Y.H. and Park D.W. (2011). A Study on Smartphone APP Authoring Solution Design for Enhancing Developer Productivity. Paper Presented at 5th International Conference on Convergence and Hybrid Information Technology(ICHIT). Daejeon: Korea.
  • Chanwimalueng W. and Kasemsan M.K. (2011). The Acceptance and Satisfaction of Smartphone Users Toward Icon Concreteness and Complexity. Proceeding of 16th Business Information Management Conference on Innovation and Knowledge Management a Global Competitive Advantage: 783-790.
  • Chen J.V., Yen D.J. and Chen K. (2009). The Acceptance and Diffusion of the Innovative Smart Phone Use: A Case Study of a Delivery Service Company in Logistics. Information and Management, 46(4): 241-248.
  • Chhablani J., Kaja S. and Shah V.A. (2012). Smartphone in Ophthalmology. Indian Journal of Ophthalmology, 60(2): 127-131.
  • Chun S.G., Chung D. and Shin Y.B. (2013). Are Students Satisfied With The Use Of Smartphone Apps? Issues in Information Systems, 14(2): 23-33.
  • DiStefano C. Zhu M., and Mindrila D. (2009). Understanding and Using Factor Scores: Considerations for the Applied Researcher. Practical Assessment, Research and Evaluation, 14(20): 1-11.
  • Eom S.J. and Kim J.H. (2014). The Adoption of Public Smartphone Applications in Korea: Empirical Analysis on Maturity Level and Influential Factors. Government Information Quarterly, 31(1): 26-36.
  • Fabrigar L.R. and Wegener D.T. (2011). Exploratory Factor Analysis: New York.
  • Ford C.M. (2012). Smartphone Apps on the Mobile Web: An Exploratory Case Study of Business Models. Business Administration Dissertation, Georgia State University. (Retrieved January 18, 2016, from http://scholarworks.gsu.edu/bus_admin_diss/14)
  • Ford J.K., MacCallum R.C. and Tait M. (1986). The Application of Exploratory Factor Analysis in Applied Psychology: A Critical Review and Analysis. Personnel Psychology, 39(2): 291-314.
  • Gerogiannis V.C., Papadopoulou S. and Papageorgiou E.I. (2012). A Fuzzy Cognitive Map for Identifying User Satisfaction from Smartphones. Paper Presented at Informatics (PCI), 16th Panhellenic Conference. (Retrieved January 18, 2016, from http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6377384&tag=1)
  • GfK TEMAX. (2015). Results for GfK TEMAX® Turkey for the Third Quarter of 2015. (Retrived December 15, 2015, from http://temax.gfk.com/fileadmin/user_upload/microsites/temax/tr/2015-Q3_GfK_TEMAX_Press_Release_Turkey_en.pdf)
  • Herrington A. (2009). Using a Smartphone to Create Digital Teaching Episodes as Resources in Adult Education. Chap. 3 in New Technologies, New Pedagogies: Mobile Learning in Higher Education. University of Wollongong: Australia.
  • Hosmer D.W. and Lemeshow S. (2000). Applied Logistic Regression: New Jersey.
  • Hsu, C.I., Chiu C. and Hsu W.L. (2013). Usability Evaluation and Correspondence Analysis of Smartphone Operating Systems. Paper Presented at the 13th International Conference on Electronic Business. Singapore.
  • Hutcheson G.D. and Soproniou N. (1999). The Multivariate Social Scientist: Introductory Statistics Using Genaralized Linear Models: London.
  • Hwang Y.H., Moon Y.J. and Hwang W.T. (2013). Effects of Users’ Values on Users’ Satisfaction and Intention to Use of Smartphone Games. Proceeding of International Conference on International Conference on Convergence Technology 2(1): 1290-1291.
  • IDC. (2015). Smartphone OS Market Share, Q1 2015. (Retrieved July 21, 2015, from http://www.idc.com/prodserv/smartphone-os-market-share.jsp)
  • Jöreskog K.G. (2003) Factor Analysis by MINRES. Scientific Software International: Chicago. (Retrieved April 7, 2011, from http://www.ssicentral.com/lisrel/techdocs/minres.pdf)
  • Kang S. and Jung J. (2014). Mobile Communication for Human Needs: A Comparison of Smartphone Use Between the US and Korea. Computers in Human Behavior, 35: 376-387.
  • Lee J.Y., Kim W.H. and Kim C.R. (2011). Measuring Service Quality and Customer Satisfaction in Online Trading Services on Smartphones. Paper Presented at 3rd International Conference on Communication Software and Networks. China.
  • McTavish F.M., Chic M.Y., Shah D. and Gustafson D.H. (2012). How Patients Recovering from Alcoholism Use a Smartphone Intervention. Journal of Dual Diagnosis, 8(4): 294-304
  • Meyer, L.S., Gamst G. and Guarino A.J. (2006). Applied Multivariate Research: Design and Interpretation: USA.
  • Michael B.D. and Geleta D. (2013). Development of Clickclinica: A Novel Smartphone Application to Generate Real-Time Global Disease Surveillance and Clinical Practice Data. BMC Medical Informatics and Decision Making, 13: 70-79.
  • Möller A., Thielsch A., Dallmeier B., Roalter L., Diewald S., Hendrich A., Meyer B.E. and Kranz M. (2011). Mobidics–Improving University Education with a Mobile Didactics Toolbox. Paper Presented at Ninth International Conference on Pervasive Computing San Francisco. CA: USA.
  • Niffikeer C.I., Hewins R.D. and Flavell R.B. (2000). A Synthetic Factor Approach to the Estimation of Value-at-Risk of a Portfolio of Interest Rate Swaps. Journal of Banking and Finance, 24(12): 1903-1932.
  • Ozdalga E., Ozdalga A. and Ahuja N. (2012). The Smartphone in Medicine: A Review of Current and Potential Use Among Physicians and Students. Journal of Medical Internet Research, 14(5):e128
  • Pampel F. C. (2000). Logistic Regression: A Primer. USA.
  • Park B.W. and Lee K.C. (2011). A Pilot Study to Analyze the Effects of User Experience and Device Characteristics on the Customer Satisfaction of Smartphone Users. Proceeding of 2nd International Conference on Ubiquitous Computing and Multimedia Applications. Part II: 421-427.
  • Park S., Oh D. and Lee B.G. (2011). Analyzing User Satisfaction Factors for Instant Messenger-Based Mobile SNS. Proceeding of 6th International Conference on Future Information Technology: 280-287.
  • Payne K.F.B., Wharred H. and Watts K. (2012). Smartphone and Medical Related App Use Among Medical Students and Junior Doctors in the United Kingdom (UK): A Regional Survey. BMC Medical Informatics and Decision Making, 12: 121-131.
  • Peng C.Y.J., Lee K.L. and Ingersoll G.M. (2002). An Introduction to Logistic Regression Analysis and Reporting. The Journal of Educational Research, 96(1): 3-14.
  • Peng C.Y.J. and So T.S.H. (2002). Logistic Regression Analysis and Reporting: A Primer. Teaching Articles. Understanding Statistics, 1(1): 31-70.
  • Peslak A., Shannon L.J. and Ceccucci W. (2011). An Empirical Study of Cell Phone and Smartphone Usage. Issues in Information Systems, 12(1): 407-417.
  • Polat C. and Maksudunov A. (2012). The Preferences of Young Consumers in Mobile Phone Markets: The Case of Kyrgyzstan. Paper Presented at International Conference on Eurasian Economies. Almaty. Kazakhstan.
  • Shin D.H., Shin Y.J., Choo H. and Beom K. (2011). Smartphones as Smart Pedagogical Tools: Implications for Smartphones as u-Learning Devices. Computers in Human Behavior, 27: 2207-2214.
  • Smart N.J. (2012). A Survey of Smartphone and Tablet Computer Use by Colorectal Surgeons in the UK and Continental Europe. Colorectal Disease, 14 (9): 535-538.
  • Stevens J. (2009). Applied Multivariate Statistics for the Social Sciences. USA.
  • Taner N. (2013). Kullanıcıların Akıllı Telefonları Değerlendirmeleri: Kastamonu Şehir Merkezinde Bir Uygulama. Uluslararası İşletme ve Yönetim Dergisi, 1(2): 127-140.
  • Verkasalo H. (2010). Analysis of Smartphone User Behavior. Paper of presented at Ninth International Conference on Mobile Business and Global Mobility Roundtable (ICMB-GMR): 258-263.
  • Verkasalo H., López-Nicolás C., Molina-Castillo F.J. and Bouwman H. (2010). Analysis of Users and Non-Users of Smartphone Applications. Telematics and Informatics, 27(3): 242-255.
  • Williams B., T. Brown, and A. Onsman. 2012. “Exploratory Factor Analysis: A Five-Step Guide for Novices.” Australasian Journal of Paramedicine 8(3): 1-14.
  • White J. and Turner H. (2011). Smartphone Computing in the Classroom. Pervasive Computing, IEEE, 10(2): 82-86.
  • Yu F. and Conway A.R. (2012). Mobile / Smartphone Use in Higher Education. Proceeding of the 2012 Southwest Decision Sciences Institute: 831-839.

Volume 5, Issue 1, 2017

2017.05.01.STAT.03

alphanumeric journal

Volume 5, Issue 1, 2017

Pages 147-162

Received: Dec. 9, 2016

Accepted: May 8, 2017

Published: June 30, 2017

Full Text [467.6 KB]

  • Share

2017 Şamkar, H.

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

Creative Commons Attribution licence

scan QR code to access this article from your mobile device


Contact Us

School of Transportation and Logistics, Istanbul University
Avcilar Campus 34320 Avcilar/Istanbul/TURKEY

Bahadır Fatih Yıldırım, Ph.D.
editor@alphanumericjournal.com
+ 90 (212) 473 70 00 - 19263

alphanumeric journal

alphanumeric journal has been publishing as "International Peer-Reviewed Journal" every six months since 2013. alphanumeric serves as a vehicle for researchers and practitioners in the field of quantitative methods, and is enabling a process of sharing in all fields related to the operations research, statistics, econometrics and management informations systems in order to enhance the quality on a globe scale.