Akıllı Telefon Tasarımına Etki Eden Parametrelerin Bulanık Kano Modeli İle Analizi

Gelişen teknolojiyle birlikte mobil telefonlara internete erişim imkânı sağlanmış ve bu da mobil telefonların kullanımı yaygınlaştırmıştır. Çeşitli firmalar farklı mobil telefon tasarımlarını çeşitli ürün özellikleriyle birlikte küresel pazara sunmaktadır. Ancak sunulan bu özelliklerin müşteri beklentisi ve algısı açısından önemi belirsizdir. Bu nedenle, bu çalışmanın kapsamında, mobil telefon tasarım özelliklerini kullanıcı algısı ve beklentisi doğrultusunda sınıflandırması amaçlanmaktadır. Böylece üreticilerin kullanıcı beklentisi ve algısına yönelik tasarımlarını geliştirme imkânı sunulacaktır. Çalışma kapsamında bulanık Kano Modeli yöntemiyle telefon tasarım parametreleri sınıflandırılmış ve elde edilen sınıflandırma klasik Kano Modeli yöntemiyle kıyaslanmıştır. Son zamanlarda işletmelerin pazara sundukları mobil telefon tasarımlarında ön plana çıkan özelliklerin kullanıcı açısından önemini tanımlamak amacıyla Kano Model anketleri hazırlanmış ve bu anketler 18-35 yaş arasında değişen 118 katılımcıya uygulanmıştır.

Analysis of Parameters Affecting The Smart Phone Design by Using Fuzzy Kano Model

Mobile phones have been popular by providing with access to the internet based on evolving technology. On the global market, various companies offer different mobile phone designs with various product features. However, the significance of these features with regards to customer expectations and perception is uncertain. For this, within the scope of this study, it is aimed to classify mobile phone design features in the direction of user perception and expectation. This will allow manufacturers to develop customer expectation and perception oriented designs. In the scope of the study, the telephone design parameters were classified by using fuzzy Kano Model and the obtained classification was compared with results obtained from classic Kano Model. Kano Model surveys have been prepared to define the importance of user-oriented features in the mobile phone designs that have been recently introduced to the market and these surveys have been applied to 118 participants between 18-35 years old.

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  • Budiarto, Nishio, S., Tsukamoto, M., 2002. Data management issues in mobile and peer-to-peer environments. Data and Knowledge Engineering, 41, 183– 204.
  • Chang, Y. F., Chen, C.S., Zhou, H., 2009. Smart phone for mobile commerce. Computer Standards & Interfaces, 31, 4, 740-747.
  • Chang, Y.F., Chen, C.S., 2005. Smart phone—the choice of client platform for mobile commerce. Computer Standards & Interfaces, 27(4), 329-336.
  • Chen, D-N., Hu, P. J-H., Kuo R-Y., Liang T-P., 2010. A Web-based personalized recommendation system for mobile phone selection: Design, implementation, and evaluation. Expert Systems with Applications, 37, 8201–8210
  • Chen, K., Chen, J.V., Yen, D. C., 2011. Dimensions of self-efficacy in the study of smart phone acceptance. Computer Standards & Interfaces, 33, 4, 422-431.
  • Çebi, S., 2013a. Determining Importance Degrees of Website Design Parameters Based on Interactions and Types of Websites. Decision Support Systems, 54 (2), 1030–1043.
  • Çebi, S., 2013b. A Quality Evaluation Model for the Design Quality of Online Shopping Websites. Electronic Commerce Research and Applications, 12 (2), 124–135.
  • Gedik N., Karademirci A.H., Kursun E., Cagiltay K., 2012. Key instructional design issues in a cellular phone-based mobile learning project. Computers & Education, 58, 1149–1159.
  • Ilbahar, E., & Cebi, S., 2017. Classification of design parameters for E-commerce websites: A novel fuzzy Kano approach. Telematics and Informatics, 34(8), 1814-1825.
  • Janković, B., Nikolić, M., Vukonjanski, J., Terek, E., 2016. The impact of Facebook and smart phone usage on the leisure activities and college adjustment of students in Serbia. Computers in Human Behavior, 55, Part A, 354-363.
  • Kano, N., 1984. Attractive quality and must-be quality. Hinshitsu (Quality, The Journal of Japanese Society for Quality Control), 14, 39-48.
  • Kim, T., Jung, E. S., Im, Y., 2014. Optimal control location for the customer-oriented design of smart phones. Information Sciences, 257, 264-275.
  • Kim, T.-H., Jin S.-H., 2015. Development of auditory design guidelines for improving learning on mobile phones. Computers & Education, 91, 60-72.
  • Lee, Y. C., & Huang, S. Y., 2009. A new fuzzy concept approach for Kano’s model. Expert Systems with Applications, 36(3), 4479-4484.
  • Lee, Y. C., Sheu, L. C., & Tsou, Y. G., 2008. Quality function deployment implementation based on Fuzzy Kano model: An application in PLM system. Computers & Industrial Engineering, 55(1), 48-63.
  • Lin Y.-C., Lai H-H., Yeh, C-H., 2007. Consumer-oriented product form design based on fuzzy logic: A case study of mobile phones. International Journal of Industrial Ergonomics, 37, 531–543
  • Lu, E.J.-L., Cheng, Y.-Y., 2004. Design and implementation of a mobile database for Java phones. Computer Standards & Interfaces, 26, 401–410.
  • Mikulić, J., Prebežac, D., 2011. A critical review of techniques for classifying quality attributes in the Kano model. Managing Service Quality: An International Journal, 21(1), 46-66.
  • Özbek, V., Alnıaçık, Ü., Koc, F., Akkılıç, M. E., Kaş, E., 2014. The Impact of Personality on Technology Acceptance: A Study on Smart Phone Users. Procedia - Social and Behavioral Sciences, 150, 541-551.
  • Parsons, D., Ryu, H., Cranshaw, M., 2007. A design requirements framework for mobile learning environments. Journal of Computers, 2(4), 1-8.
  • Rhee, H., Kim, S., 2016, Effects of breaks on regaining vitality at work: An empirical comparison of ‘conventional’ and ‘smart phone’ breaks. Computers in Human Behavior, 57, 160-167,
  • Wang, C. H., 2013. Incorporating customer satisfaction into the decision-making process of product configuration: a fuzzy Kano perspective. International Journal of Production Research, 51(22), 6651-6662.
  • Wang, C. H., & Wang, J., 2014. Combining fuzzy AHP and fuzzy Kano to optimize product varieties for smart cameras: A zero-one integer programming perspective. Applied Soft Computing, 22, 410-416.
  • Wang, X., Ruan, D., Kerre, E. E., 2009. Mathematics of fuzziness—Basic issues, Vol. 245, Springer Science &Business Media.
  • Wu, Y.-H., ve Ho C.C., 2015. Integration of green quality function deployment and fuzzy theory: a case study on green mobile phone design. Journal of Cleaner Production, 108, 271-280.
  • Yang, C.-C., Chang H.-C., 2012. Selecting representative affective dimensions using Procrustes analysis: An application to mobile phone design. Applied Ergonomics, 43, 1072-1080.
  • Zadeh, L. A., 1965. Information and control. Fuzzy sets, 8(3), 338-353.