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CONSUMERS WHITE AUTOMOBILE PURCHASE BEHAVIOR: TURKEY AUTOMOBILE MARKET APPLICATION WITH SWARA METHOD

Year 2022, , 43 - 64, 29.04.2022
https://doi.org/10.18070/erciyesiibd.918762

Abstract

The automobile industry is one of the leading commercial markets around the world. In this enormous market, countries, companies, and manufacturers compete boldly to increase their international market shares. In this great competition, there are centuries old giant companies such as Mercedes, BMW, Volkswagen, Opel, as well as new automobile brands such as Tesla, Renovo, Tritonev. Turkey is one of the significant markets where these brands are competing fiercely. When this market is analyzed, one preference of Turkish consumers draws much attention. This is the color preferences of automobile purchasers. Considering the sales figures of the previous years, white automobile sales are above 50% rate regardless of brand and model. The objective of this study investigated why Turkish automobile consumers prefer white automobile color. In this study, the SWARA method, one of the MCDM method is used to analyze consumers white automobile preferences. The findings of the study show that aesthetic perceptions are significant in purchasing white automobiles. The results of the study allow us to draw implications for the white automobile purchasing behavior for the global automobile market in the concept of international marketing.

References

  • Apak, S., Göğüş, G. G., and Karakadılar, İ. S. (2012). An analytic hierarchy process approach with a novel framework for luxury car selection. Procedia-Social and Behavioral Sciences, 58, 1301–1308. Arslan, İ. K. (2003). Otomobil alımında tüketici davranışlarını etkileyen faktörler.
  • Axalta Coating Systems. (2015). Global Automotive 2015 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Axalta Coating Systems. (2016). Global Automotive 2016 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Axalta Coating Systems. (2017). Global Automotive 2017 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Axalta Coating Systems. (2018). Global Automotive 2018 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Axalta Coating Systems. (2019a). Global Automotive 2019 Color Popularity Report.
  • Axalta Coating Systems. (2019b). Global Automotive 2019 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Babolhavaeji, M., Vakilian, M. A. and Slambolchi, A. (2015). The role of product color in consumer behavior. Advanced Social Humanities and Management, 2(1), 9–15.
  • Bellizzi, J. A. and Hite, R. E. (1992). Environmental color, consumer feelings, and purchase likelihood. Psychology and Marketing, 9(5), 347–363.
  • Berkovec, J. (1985). New car sales and used car stocks: A model of the automobile market. The Rand Journal of Economics, 195–214.
  • Byun, D.-H. (2001). The AHP approach for selecting an automobile purchase model. Information and Management, 38(5), 289–297.
  • Chand, M. and Avikal, S. (2015, November). An MCDM based approach for purchasing a car from Indian car market. In 2015 IEEE Students Conference on Engineering and Systems (SCES) (pp. 1-4). IEEE.
  • Che Jamil, F. and Shariff Adli Aminuddin, A. (2019). Preliminary study of Malaysian eco-friendly car selection by using analytic hierarchy process. Journal of Physics: Conference Series, 1218(1), 1–8. https://doi.org/10.1088/1742-6596/1218/1/012022
  • Doğan, Ö. İ., Marangoz, M. and Topoyan, M. (2003). İşletmelerin İç ve Dış Pazarda Rekabet Gücünü Etkileyen Faktörler ve Bir Uygulama. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 2(5), 114–139.
  • Güngör, İ. and İşler, D. B. (2005). Analitik Hiyerarşi Yaklaşımı ile Otomobil Seçimi. Zonguldak Karaelmas Üniversitesi Sosyal Bilimler Dergisi, 1(2), 21–33.
  • Hackbarth, A. and Madlener, R. (2013). Consumer preferences for alternative fuel vehicles: A discrete choice analysis. Transportation Research Part D: Transport and Environment, 25, 5–17.
  • Hamurcu, M. and Eren, T. (2018). A hybrid approach of analytic hierarchy process-topsıs and goal programming for electric automobile selection. The 2018 International Conference of the African Federation of Operational Research Societies (AFROS 2018).
  • Keršuliene, V., Zavadskas, E. K. and Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
  • Patil, A. N., Pai Bhale, N. G., Raikar, N. and Prabhakaran, M. (2017). Car selection using hybrid fuzzy ahp and grey relation analysis approach. International Journal of Performability Engineering, 13(5), 569–576. https://doi.org/10.23940/ijpe.17.05.p2.569576
  • Raut, R. D., Bhasin, H. V. and Kamble, S. S. (2011). Multi-criteria decision-making for automobile purchase using an integrated analytical quality fuzzy (AQF) technique. International Journal of Services and Operations Management, 10(2), 136–167. https://doi.org/10.1504/IJSOM.2011.042515
  • Rohit Singh, R. and Avikal, S. (2019). Review of Deep Learning Techniques. Advances in Intelligent Systems and Computing, 741(A MCDM-Based Approach for Selection of a Sedan Car from Indian Car Market), 569–578. https://doi.org/10.1007/978-981-13-0761-4
  • Roy, S., Mohanty, S. and Mohanty, S. (2018). An Efficient Hybrid MCDM Based Approach for Car Selection in Automobile Industry. Proceedings of the 2018 3rd IEEE International Conference on Research in Intelligent and Computing in Engineering, RICE 2018, Promethee Ii, 1–5. https://doi.org/10.1109/RICE.2018.8509065
  • Saaty, T. L. (1980). The Analytic Hierarchy Process. Education, 1–11. https://doi.org/10.3414/ME10-01-0028
  • Salter, C. A. and Salter, C. D. (1982). Automobile color as a predictor of driving behavior. Perceptual and Motor Skills, 55(2), 383–386.
  • Sambandam, R. and Lord, K. R. (1995). Switching behavior in automobile markets: a consideration-sets model. Journal of the Academy of Marketing Science, 23(1), 57–65.
  • Stanujkic, D., Karabasevic, D. and Zavadskas, E. K. (2015). A framework for the selection of a packaging design based on the SWARA method. Inzinerine Ekonomika-Engineering Economics, 26(2), 181–187.
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute) (2016). "Motorlu Kara Taşıtları Sayı: 21600" Raporu (Motor Land Vehicles News Bulletin 2015 Number: 21600. http://www.oyder-tr.org/ Content/document/raporlar/tuik-raporlari/tuik-motorlu-kara-tasitlari-raporu-haber-bulteni-2015.pdf
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute), 2017. www.tuik.gov.tr. “Motorlu Kara Taşıtları Haber Bülteni 2016 Sayı: 24595" (Motor Land Vehicles News Bulletin 2016 Number: 24595).
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute), (2018a). www.tuik.gov.tr. "Motorlu Kara Taşıtları Haber Bülteni 2017 Sayı: 27640" (Motor Land Vehicles News Bulletin 2017 Number: 27640).
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute), (2018b). www.tuik.gov.tr. “Motorlu Kara Taşıtları Haber Bülteni 2018 Sayı: 27663" (Motor Land Vehicles News Bulletin 2018 Number: 27663).
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute), (2020a). www.tuik.gov.tr. “Motorlu Kara Taşıtları Haber Bülteni 2019 Sayı: 33648" (Motor Land Vehicles News Bulletin 2019)
  • Türkiye İstatistik Kurumu. (2020b). (Turkish Statistical İnstitute), (2020b). www.tuik.gov.tr. “Motorlu Kara Taşıtları Haber Bülteni 2020 Sayı: 33655" (Motor Land Vehicles News Bulletin 2020 Number: 33655) Ulkhaq, M. M., Wijayanti, W. R., Zain, M. S., Baskara, E. and Leonita, W. (2018). Combining the AHP and TOPSIS to evaluate car selection. ACM International Conference Proceeding Series, Car Selection, 112–117. https://doi.org/10.1145/3195612.3195628
  • Ulutaş, A., Karakuş, C. B. and Topal, A. (2020). Location selection for logistics center with fuzzy SWARA and cocoso methods. Journal of Intelligent & Fuzzy Systems, Preprint, 1–17.
  • Verboven, F. (1999). Product line rivalry and market segmentation—with an application to automobile optional engine pricing. The Journal of Industrial Economics, 47(4), 399–425.
  • Vidyavathi, K. (2012). Consumer Lifestyle Influence of Consumer Behavior with reference to automobile industry in Chennai. Zenith International Journal of Multidisciplinary Research, II (4), 37–50.
  • Yildiz, A. and Ergul, E. U. (2014). Usage of Fuzzy Multi-criteria decisionmaking method to solve the automobile selection problem. Journal of Engineering and Fundamentals, 1-10.

TÜKETICILERİN BEYAZ OTOMOBİL SATIN ALMA DAVRANIŞI: SWARA YÖNTEMİ İLE TÜRKIYE OTOMOBIL PAZARI UYGULAMASI

Year 2022, , 43 - 64, 29.04.2022
https://doi.org/10.18070/erciyesiibd.918762

Abstract

Otomobil endüstrisi, dünyanın önde gelen ticari pazarlarından biridir. Bu devasa pazarda ülkeler, şirketler ve üreticiler uluslararası pazar paylarını artırmak için cesurca rekabet etmektedirler. Bu büyük rekabette Mercedes, BMW, Volkswagen, Opel gibi asırlık dev firmaların yanı sıra Tesla, Renovo, Tritonev gibi yeni otomobil markaları da yer almaktadır. Türkiye, bu markaların kıyasıya rekabet ettiği önemli pazarlardan biridir. Bu pazar incelendiğinde Türk tüketicisinin bir tercihi çok dikkat çekmektedir. Bu, otomobil satin alan kişilerin renk tercihleridir. Geçmiş yılların satış rakamlarına bakıldığında beyaz otomobil satışları marka ve model fark etmeksizin % 50'nin üzerinde olduğu görülmektedir. Bu çalışmanın amacı, Türk otomobil tüketicilerinin neden beyaz otomobil rengini tercih ettiklerinin analizini yapmaktır. Bu çalışmada tüketicilerin beyaz otomobil tercihlerini analiz etmek için ÇKKV yöntemlerinden biri olan SWARA yöntemi kullanılmıştır. Araştırmanın bulguları, beyaz renk otomobil satın alırken estetik algıların ön plana çıktığını göstermiştir. Çalışmanın sonuçları, uluslararası pazarlama konseptinde küresel otomobil pazarı için beyaz otomobil satın alma davranışına ilişkin çıkarımlar yapılmasını sağlamaktadır.

References

  • Apak, S., Göğüş, G. G., and Karakadılar, İ. S. (2012). An analytic hierarchy process approach with a novel framework for luxury car selection. Procedia-Social and Behavioral Sciences, 58, 1301–1308. Arslan, İ. K. (2003). Otomobil alımında tüketici davranışlarını etkileyen faktörler.
  • Axalta Coating Systems. (2015). Global Automotive 2015 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Axalta Coating Systems. (2016). Global Automotive 2016 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Axalta Coating Systems. (2017). Global Automotive 2017 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Axalta Coating Systems. (2018). Global Automotive 2018 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Axalta Coating Systems. (2019a). Global Automotive 2019 Color Popularity Report.
  • Axalta Coating Systems. (2019b). Global Automotive 2019 Color Popularity Report. https://www.axalta.com/content/dam/New Axalta Corporate
  • Babolhavaeji, M., Vakilian, M. A. and Slambolchi, A. (2015). The role of product color in consumer behavior. Advanced Social Humanities and Management, 2(1), 9–15.
  • Bellizzi, J. A. and Hite, R. E. (1992). Environmental color, consumer feelings, and purchase likelihood. Psychology and Marketing, 9(5), 347–363.
  • Berkovec, J. (1985). New car sales and used car stocks: A model of the automobile market. The Rand Journal of Economics, 195–214.
  • Byun, D.-H. (2001). The AHP approach for selecting an automobile purchase model. Information and Management, 38(5), 289–297.
  • Chand, M. and Avikal, S. (2015, November). An MCDM based approach for purchasing a car from Indian car market. In 2015 IEEE Students Conference on Engineering and Systems (SCES) (pp. 1-4). IEEE.
  • Che Jamil, F. and Shariff Adli Aminuddin, A. (2019). Preliminary study of Malaysian eco-friendly car selection by using analytic hierarchy process. Journal of Physics: Conference Series, 1218(1), 1–8. https://doi.org/10.1088/1742-6596/1218/1/012022
  • Doğan, Ö. İ., Marangoz, M. and Topoyan, M. (2003). İşletmelerin İç ve Dış Pazarda Rekabet Gücünü Etkileyen Faktörler ve Bir Uygulama. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 2(5), 114–139.
  • Güngör, İ. and İşler, D. B. (2005). Analitik Hiyerarşi Yaklaşımı ile Otomobil Seçimi. Zonguldak Karaelmas Üniversitesi Sosyal Bilimler Dergisi, 1(2), 21–33.
  • Hackbarth, A. and Madlener, R. (2013). Consumer preferences for alternative fuel vehicles: A discrete choice analysis. Transportation Research Part D: Transport and Environment, 25, 5–17.
  • Hamurcu, M. and Eren, T. (2018). A hybrid approach of analytic hierarchy process-topsıs and goal programming for electric automobile selection. The 2018 International Conference of the African Federation of Operational Research Societies (AFROS 2018).
  • Keršuliene, V., Zavadskas, E. K. and Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
  • Patil, A. N., Pai Bhale, N. G., Raikar, N. and Prabhakaran, M. (2017). Car selection using hybrid fuzzy ahp and grey relation analysis approach. International Journal of Performability Engineering, 13(5), 569–576. https://doi.org/10.23940/ijpe.17.05.p2.569576
  • Raut, R. D., Bhasin, H. V. and Kamble, S. S. (2011). Multi-criteria decision-making for automobile purchase using an integrated analytical quality fuzzy (AQF) technique. International Journal of Services and Operations Management, 10(2), 136–167. https://doi.org/10.1504/IJSOM.2011.042515
  • Rohit Singh, R. and Avikal, S. (2019). Review of Deep Learning Techniques. Advances in Intelligent Systems and Computing, 741(A MCDM-Based Approach for Selection of a Sedan Car from Indian Car Market), 569–578. https://doi.org/10.1007/978-981-13-0761-4
  • Roy, S., Mohanty, S. and Mohanty, S. (2018). An Efficient Hybrid MCDM Based Approach for Car Selection in Automobile Industry. Proceedings of the 2018 3rd IEEE International Conference on Research in Intelligent and Computing in Engineering, RICE 2018, Promethee Ii, 1–5. https://doi.org/10.1109/RICE.2018.8509065
  • Saaty, T. L. (1980). The Analytic Hierarchy Process. Education, 1–11. https://doi.org/10.3414/ME10-01-0028
  • Salter, C. A. and Salter, C. D. (1982). Automobile color as a predictor of driving behavior. Perceptual and Motor Skills, 55(2), 383–386.
  • Sambandam, R. and Lord, K. R. (1995). Switching behavior in automobile markets: a consideration-sets model. Journal of the Academy of Marketing Science, 23(1), 57–65.
  • Stanujkic, D., Karabasevic, D. and Zavadskas, E. K. (2015). A framework for the selection of a packaging design based on the SWARA method. Inzinerine Ekonomika-Engineering Economics, 26(2), 181–187.
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute) (2016). "Motorlu Kara Taşıtları Sayı: 21600" Raporu (Motor Land Vehicles News Bulletin 2015 Number: 21600. http://www.oyder-tr.org/ Content/document/raporlar/tuik-raporlari/tuik-motorlu-kara-tasitlari-raporu-haber-bulteni-2015.pdf
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute), 2017. www.tuik.gov.tr. “Motorlu Kara Taşıtları Haber Bülteni 2016 Sayı: 24595" (Motor Land Vehicles News Bulletin 2016 Number: 24595).
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute), (2018a). www.tuik.gov.tr. "Motorlu Kara Taşıtları Haber Bülteni 2017 Sayı: 27640" (Motor Land Vehicles News Bulletin 2017 Number: 27640).
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute), (2018b). www.tuik.gov.tr. “Motorlu Kara Taşıtları Haber Bülteni 2018 Sayı: 27663" (Motor Land Vehicles News Bulletin 2018 Number: 27663).
  • Türkiye İstatistik Kurumu (Turkish Statistical İnstitute), (2020a). www.tuik.gov.tr. “Motorlu Kara Taşıtları Haber Bülteni 2019 Sayı: 33648" (Motor Land Vehicles News Bulletin 2019)
  • Türkiye İstatistik Kurumu. (2020b). (Turkish Statistical İnstitute), (2020b). www.tuik.gov.tr. “Motorlu Kara Taşıtları Haber Bülteni 2020 Sayı: 33655" (Motor Land Vehicles News Bulletin 2020 Number: 33655) Ulkhaq, M. M., Wijayanti, W. R., Zain, M. S., Baskara, E. and Leonita, W. (2018). Combining the AHP and TOPSIS to evaluate car selection. ACM International Conference Proceeding Series, Car Selection, 112–117. https://doi.org/10.1145/3195612.3195628
  • Ulutaş, A., Karakuş, C. B. and Topal, A. (2020). Location selection for logistics center with fuzzy SWARA and cocoso methods. Journal of Intelligent & Fuzzy Systems, Preprint, 1–17.
  • Verboven, F. (1999). Product line rivalry and market segmentation—with an application to automobile optional engine pricing. The Journal of Industrial Economics, 47(4), 399–425.
  • Vidyavathi, K. (2012). Consumer Lifestyle Influence of Consumer Behavior with reference to automobile industry in Chennai. Zenith International Journal of Multidisciplinary Research, II (4), 37–50.
  • Yildiz, A. and Ergul, E. U. (2014). Usage of Fuzzy Multi-criteria decisionmaking method to solve the automobile selection problem. Journal of Engineering and Fundamentals, 1-10.
There are 36 citations in total.

Details

Primary Language English
Journal Section Makaleler
Authors

Sinan Çizmecioğlu 0000-0002-3355-8882

Fatih Cura 0000-0001-8025-3961

Publication Date April 29, 2022
Acceptance Date October 13, 2021
Published in Issue Year 2022

Cite

APA Çizmecioğlu, S., & Cura, F. (2022). CONSUMERS WHITE AUTOMOBILE PURCHASE BEHAVIOR: TURKEY AUTOMOBILE MARKET APPLICATION WITH SWARA METHOD. Erciyes Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi(61), 43-64. https://doi.org/10.18070/erciyesiibd.918762

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