AKILLI TELEFON SEÇİM FAKTÖRLERİNİN BÜTÜNLEŞİK YAPISAL EŞİTLİK MODELİ - ANALİTİK HİYERARŞİ SÜRECİ İLE İNCELENMESİ

Yıl 2019, , 113 - 130, 09.04.2019

Selçuk Perçin , Mehmet Serhat Pancaroğlu

https://doi.org/10.18092/ulikidince.476865

Cited By: 3

Öz

Dünya, Dördüncü Sanayi Devrimi’ne hazırlık
yaparken; teknolojik gelişmeler büyük bir ivme kazanmıştır. Her geçen gün
büyüyen ve farklılaşan akıllı telefon pazarı gün geçtikçe gelişmekte,
seçenekler artmaktadır. Karar vermek, seçeneklerin artması ve karmaşıklaşması
nedeniyle zorlaşmaya başlamıştır. Çalışmanın amacı etkin bir Çok Kriterli Karar
Verme (ÇKKV) modeli önermektir. Bu amaçla, bütünleşik Yapısal Eşitlik Modeli
(YEM) – Analitik Hiyerarşi Süreci (AHS) kullanılmıştır. Akıllı telefon seçimini
etkileyen 4 kriter ve 16 alt kriter kullanılmıştır. Kriterler ve alt kriterler
YEM’den elde edilen bilgilere göre sıralanmıştır. Alternatiflerin alt
kriterlere göre ikili karşılaştırmaları ve alternatiflerin sıralanması ise AHS
ile gerçekleştirilmiştir. Çalışma sonucunda maliyet, fiziksel, teknik ve kalite
kriterlerinin akıllı telefon seçimi üzerinde anlamlı etkilerinin olduğu
sonucuna varılmıştır. Ayrıca, karar vericinin akıllı telefon tercihlerini en
üst düzeyde etkileyen kriter kalite, etkisi en fazla olan alt kriterler ise
marka imajı ve estetik kriterleridir. Oluşturulan model son yıllarda Türkiye ve
dünyada en fazla satış yapan iki marka üzerinde uygulanmıştır.

Anahtar Kelimeler

Akıllı Telefon, Analitik Hiyerarşi Süreci (AHS), Yapısal Eşitlik Modeli (YEM)

ANALYZING SMARTPHONE CHOOSING FACTORS WITH HYBRID STRUCTURAL EQUATION MODELLİNG – ANALYTIC HIERARCHY PROCESS

Öz

While the world is
preparing for the Fourth Industrial Revolution; technological developments have
gained momentum. The smartphone market which continues improving and
differentiating is growing day by day, and the number of options are
increasing. Making a decision has begun to become difficult because of the
number and complexity of options. The purpose of the study is to recommend an
effective Multi Criteria Decision Making (MCDM) model. For this purpose, an
integrated Structural Equation Model (SEM) - Analytic Hierarchy Process (AHP)
was used in this study. 4 criteria and 16 sub-criteria were used to influence
smartphone selection. Criteria and sub-criteria are listed according to the
results of SEM. Binary comparisons of alternatives according to sub-criteria
and ranking of alternatives were calculated with AHP. It has been reached that
cost, physical, technical and quality criteria have a significant effect on
smart phone selection, as a result. Also; quality is the criterion that affects
the decision maker's smart phone preferences at the highest level, and the
sub-criteria with the greatest effects are the brand image and esthetic. The
proposed model has been applied for two brands which have highest-selling
quantities in Turkey and also in the world, in last few years.

Anahtar Kelimeler

Smartphone, Analytic Hierarchy Process (AHP), Structural Equation Modelling (SEM)

Kaynakça

• Artvin Çoruh Üniversitesi Öğrenci Sayıları (2018). Erişim Adresi https:// www.artvin.edu.tr/uploads /oidb.artvin.edu.tr/userfiles/files/%C4%B0statistikler/N%C4%B0SAN%202018%20%C3%96%C4%9ERENC%C4%B0%20SAYILARI.pdf (18.04.2018).
• Ande, R. A. (2017). Brand Resonance Score for CBBE model: an Application in financial services. Benchmarking: An International Journal, 24(6), 1490-1507.
• Atmojo, R. N. P., Cahyani, A. D., Abbas, B. S., Pardamean, B., ve Manulang, I. D. (2014). Design of Single User Decision Support System Model Based on Fuzzy Simple Additive Weighting Algorithm to Reduce Consumer Confusion Problems in Smartphone Purchases. Applied Mathematical Sciences, 8(15), 717-732.
• Bayhan, M. ve Bildik, T. (2014) “Çok Kriterli Karar Verme Tekniklerinden Analitik Hiyerarşi Süreciyle Akıllı Telefon Seçimi”. Uluslararası Alanya İşletme Fakültesi Dergisi, 6(3), 27-36.
• Belbag, S., Gungordu, A., Yumusak, T. ve Yilmaz, K. G. (2016). The Evaluation of Smartphone Brand Choice: An Application with The Fuzzy Electre I Method. International Journal of Business and Management Invention, 5(3), 55-63.
• Beltran, J., Munuzuri, J., Rivas, M. ve Martin, E. (2014). Development of a Metrological Management Model Using The AHP and SEM Techniques. International Journal of Quality&Reliability Management, 31(7), 841-857.
• Byrne, B. M. (2010). Structural Equation Modeling with AMOS: Basic Concepts Applications and Programming (2nd ed.). New York: Routledge.
• Doğan, R., Yavuz, M., Küçükdemirci, İ. ve Eren T. (2015). Öğrencilerde Akıllı Telefon Kullanımının Özellikleri Bakımından Oyun Teorisi ile Analiz Edilmesi. Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 7(2), 67-76.
• Erinci, F. ve Sulak, H. (2014). Analitik Hiyerarşi Proses ile Akıllı Telefon Seçimi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 19(4), 225-239.
• Hasan, M., Hossain, S., Ahamed, M. K. ve Uddin, M. S. (2017). Sustainable Way of Choosing Effective Electronic Devices Using Fuzzy TOPSIS Method. American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS), 35(1), 342-351.
• Ho, F., Wang, C. N., Ho, C. T., Chiang, Y. C. ve Huang Y. F. (2015). Evaluation of Smartphone Feature Preference by A Modified AHP Approach. Industrial Engineering and Engineering Management (IEEM), 2015 IEEE International Conference, 591-594.
• Hu, S. K. Lu M. T., ve Tzeng G. H. (2014). Exploring Smart Phone Improvements Based on A Hybrid MCDM Model. Expert Systems with Applications, 41(9), 4401-4413.
• Hu, Y., Li, J., Wen, J. ve Yan Y. (2016). Evaluating Knowledge Resources in R&D Organizations in China: An Application Using Structural Equation Modeling and Analytic Hierarchy Process, Information Development, 32(3), 478-495.
• Hu, Y. C. ve Liao, Y. L. (2013). Utilizing Analytic Hierarchy Process to Analyze Consumers' Purchase Evaluation Factors of Smartphones. International Scholarly and Scientific Research & Innovation, 7(6), 1556-1561.
• Jakhar, S. K. (2014). Designing the Green Supply Chain Performance Optimisation Model. Global Journal of Flexible Systems Management, 15(3), 235-259.
• Jakhar, S. K. (2015). Performance Evaluation and a Flowal Location Decision Model for A Sustainable Supply Chain of An Apparel Industry. Journal of Cleaner Production, 87, 391-413.
• Jakhar, S. K. ve Barua, M. K. (2014). An Integrated Model Of Supply Chain Performance Evaluation and Decision Making Using Structural Equation Modelling and Fuzzy AHP. Production Planning & Control, 25(11), 938-957.
• Kecek, G. ve Yüksel, R. (2016). Analitik Hiyerarşi Süreci (AHP) ve Promethee Teknikleriyle Akıllı Telefon Seçimi. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 49, 46-63.
• Lin, S. L. ve Yang, H. L. (2014). A Three-Stage Decision Model Integrating FAHP, MDS and Association Rules for Targeting Smartphone Customers. in International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, 12-21. Cham: Springer.
• Meydan, C. H. ve Şeşen, H. (2015). Yapısal Eşitlik Modellemesi AMOS Uygulamaları (2. Baskı). Ankara: Detay Yayıncılık.
• Natasya, W. A. G. ve Kusnawi, K. (2017). Decision Support System Design to Decide on The Latest Smartphone Using Analytical Hierarchy Process. 2nd International Conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE), 456-461.
• Önder, G. ve Önder, E. (2015). Analitik Hiyerarşi Süreci. Yıldırım, B. F. ve Önder, E. (Ed.), Operasyonel Yönetsel ve Stratejik Problemlerin Çözümünde Çok Kriterli Karar Verme Yöntemleri (2. Baskı), 21-64,. Bursa: Dora Yayınevi.
• Özbek, A. (2017). Çok Kriterli Karar Verme Yöntemleri ve Excel ile Problem Çözümü (1. Baskı). Ankara: Seçkin Yayınevi.
• Özçalıcı, M. (2017). Matlab ile Çok Kriterli Karar Verme Teknikleri (1. Baskı). Ankara: Nobel Yayınevi.
• Paksoy, S. (2017). Çok Kriterli Karar Vermede Güncel Yaklaşımlar (1. Baskı). Adana: Karahan Kitabevi.
• Pipatprapa, A., Huang, H. H. ve Huang C. H. (2016a). An Integrated Approach for Developing Environmental Performance Evaluation of Taiwan’s Food Industry. International Journal of Scientific&Technology Research, 5(6), 301-305.
• Pipatprapa, A., Huang, H. H. ve Huang C. H. (2016b), “A Novel Environmental Performance Evaluation of Thailand’s Food Industry Using Structural Equation Modeling and Fuzzy Analytic Hierarchy Techniques”, Sustainability, 8(3), 246.
• Punniyamoorty, M., Mathiyalagan, P. ve Lakshmi G. (2012). A Combined Application of Structural Equation Modeling (SEM) and Analytic Hierarchy Process (AHP) in Supplier Selection. Benchmarking: An International Journal, 19(1), 70-92.
• Punniyamoorthy, M., Mathiyalagan, P. ve Parthiban P. (2011). A Strategic Model Using Structural Equation Modeling and Fuzzy Logic in Supplier Selection, Expert Systems with Applications, 38(1), 458-474.
• Ravikumar, M. M., Marimuthu, K., Parthiban P. ve Abdulzubar H. (2013). Leaness Evaluation in 6 Manufacturing SME's Using AHP and SEM Techniques. International Business Management, 7(6), 500-507.
• Saaty, T. L. (1990). How to Make A Decision: The Analytic Hierarchy Process. European Journal of Operational Research, 48(1), 9-26.
• Saaty, T. L. ve Vargas L. G. (2012). Models Methods Concepts & Applications of The Analytic Hierarchy Process (Vol. 175) (2nd Ed.). New York: Springer Science and Business Media.
• Trivedi, A., Chauhan A. ve Trivedi V. (2014). Using Fuzzy Extension of Hybrid MCDM Techniques to Evaluate Smartphones on Qualitative Dimensions. International Marketing Conference. Kolkata. Erişim adresi https://www.researchgate.net/profile/Ashish_Trivedi11/publication/315713452_Title_Using_fuzzy_extension_of_hybrid_MCDM_techniques_to_evaluate_smartphones_on_qualitative_dimensions/links/58de13d4458515add901ecc0/Title-Using-fuzzy-ext ension-of-hybrid-MCDM-techniques-to-evaluate-smartphones-on-qualitative-dimensions.pdf (04.04.2018).
• Yildiz, A. ve Ergul, E. U. (2015). A Two-Phased Multi Criteria Decision Making Approach for Selecting The Best Smartphone. South African Journal of Industrial Engineering, 26(3), 194-215.
• Yu, C. S. (2002). A GP-AHP Method for Solving Group Decision-Making Fuzzy AHP Problems. Computers & Operations Research, 29(14), 1969-2001.