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Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama

Year 2022, , 269 - 289, 25.10.2022
https://doi.org/10.17233/sosyoekonomi.2022.04.15

Abstract

Literatürde bu konuda yapılan çalışmaların eksikliği nedeniyle konu ele alınmıştır. Çalışma; tüketicilerin alışveriş alışkanlıkları ile çevrimiçi açık artırma hizmetlerinin kullanımı, hizmet kalitesinde yaşanan sorunların belirlenmesi, tüketicinin istek ve ihtiyaçlarının belirlenerek tüketicilere uygun zaman tasarrufu sağlayan ve yenilikçi hizmetin oluşturulması amacıyla hazırlanmıştır. Tüketiciden tüketiciye açık artırma sistemlerine kapsamlı yaklaşmayı, tüketicilerin e-açık artırma siteleri hakkındaki tutumlarını belirlemeyi amaçladığı için önem arz etmektedir. Anket yöntemi kullanılarak veri toplanmış ve toplanan veriler üzerinde faktör ve Anova analizi uygulaması yapılmıştır. Tüketicilerin açık artırma siteleri hakkındaki düşünceleri “güven”, “satın alma süreci”, “rekabet”, “bütçe” faktörleri çerçevesinde değerlendirilmiştir. Tüketicilerin faktör ve Anova testleri ile tüketici davranışları üzerinde “güven” P: 0,047 < 0,05 gelire bağlı olarak anlamlı şekilde farklılık gösterdiği, “satın alma süreci” P: 0,013 < 0,05 yaşa bağlı olarak anlamlı farklılık olduğu, “rekabet”, P:0,032 <0,05 cinsiyete bağlı olarak anlamlı, “bütçe” P: 0,046 < 0,05) gelire ve eğitime (F: 3, 422 - P: 0,031 <0,05) bağlı olarak anlamlı bir şekilde farklılık gösterdiği tespit edilmiştir.

Supporting Institution

-

Project Number

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References

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An Application on Determining the Consumers' Attitudes Towards Auction Sites

Year 2022, , 269 - 289, 25.10.2022
https://doi.org/10.17233/sosyoekonomi.2022.04.15

Abstract

The context was discussed due to the deficiencies in the literature and current issue on this subject. The study aims to determine consumers’ shopping habits with online auction services, specify the problems experienced in service quality, and create an innovative and time-saving service suitable for consumers by choosing their wishes and needs. This study is significant as it aims to comprehensively approach consumer-to-consumer auction systems and determine consumers' attitudes towards e-auction sites. Data were collected using the survey method, and the factor and Anova analysis were applied to the collected data. Consumers' opinions about auction sites were evaluated within the framework of factors such as “trust”, “purchasing process”, “competition”, and “budget”. According to aspect and Anova tests of consumers on consumer behaviour; it is revealed that “Trust” with P: 0.047 < 0.05 shows a significant difference depending on income, and “purchasing process” with P: 0.013 < 0.05 has a considerable difference depending on age, “competition” with P:0.032 <0.05 has a significant difference depending on gender, “budget” with P: 0.046 < 0.05 has a considerable difference depending on income and education (F: 3.422 - P: 0.031 <0.05).

Project Number

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References

  • Abdul G.E. et al. (2011), “Emic and etic interpretations of engagement with a consumer-to-consumer online auction site”, Journal of Business Research, 64, 1060-1066.
  • Andrews, T. & C. Benzing (2007), “The determinants of price in internet auctions of used cars”, Atlantic Economic Journal, 35(1), 43-57.
  • Angeloni, S. & C. Rossi (2021), “An analytical model for comparing the profitability of competing online marketing channels: Search engine marketing versus e-commerce marketplace”, Journal of Marketing Theory and Practice, 29(4), 534-549.
  • Arefeva, A. & D. Meng (2021), “Revealing information in auctions: The optimal auction versus the second-price auction”, Economics Letters, 204, 1-4.
  • Ashenfelter, O. (1989), “How auctions work for wine and art”, Journal of Economic Perspectives, 3(3), 23-36.
  • Back, K. & J.F. Zender (1993), “Auctions of divisible goods: On the rationale for the treasury experiment”, The Review of Financial Studies, 6(4), 733-764.
  • Bajari, P. & J. Yeo (2009), “Auction design and tacit collusion in FCC spectrum auctions”, NBER Working Paper Series: 14441.
  • Bakos, J.Y. (1997), “Reducing buyer search costs: Implications for electronic marketplaces”, Management Science, 43(12), 1676-1692.
  • Baranowski, P. et al. (2018), “Whose feedback matters? Empirical evidence from online auctions”, Applied Economics Letters, 25(17), 1226-1229.
  • Bei, L.T. & M.Y. Chen (2015), “The effects of hedonic and utilitarian bidding values on e-auction behavior”, Electronic Commerce Research, 15(4), 483-507.
  • Boyacıgil, B. (2008), “İnternette pazarlama açısından müzayede siteleri ve tüketicilerin müzayede siteleri hakkındaki tutumları”, Yüksek Lisans Tezi, Yıldız Teknik Üniversitesi, Sosyal Bilimler Enstitüsü.
  • Branco, F. (2001), “On the superiority of the multiple round ascending bid auction”, Economics Letters, 70(2), 187-194.
  • Cason, T.N. & L. Gangadharan (2004), “Auction design for voluntary conservation programs”, American Journal of Agricultural Economics, 86(5), 1211-1217.
  • Chang, H.H. (2010), “Task-technology fit and user acceptance of online auction”, International Journal of Human-Computer Studies, 68(1-2), 69-89.
  • Che, Y.K. (1993), “Design Competition through Multidimensional Auctions”, The RAND Journal of Economies, 24(4), 668-680.
  • Chen, C.C. & J.Y. Yao (2018), “What drives impulse buying behaviors in a mobile auction? The perspective of the Stimulus-Organism-Response model”, Telematics and Informatics, 35(5), 1249-1262.
  • Chen, J.V. et al. (2016), “The antecedents of purchase and re-purchase intentions of online auction consumers”, Human Behavior, 54, 186-196.
  • Chiou, L. & J. Pate (2018), “Trust, reputation and bidding behaviour in online mystery auctions”, Applied Economics Letters, 25(10), 702-706.
  • Chu, H. & S. Liao (2007), “Exploring consumer resale behavior in C2C online auctions: taxonomy and influences on consumer decisions”, Academy of Marketing Science Review, 11(3), 1-25.
  • Coatney, K.T. et al. (2012), “Auction prices, market share, and a common agent”, Journal of Economic Behavior, 81(1), 61-73.
  • Cramton, P. et al. (1987), “Dissolving a partnership efficiently”, Econometrica, 55(3), 615-632.
  • Cui, X. et al. (2008), “Research on consumer behaviour in online auctions: Insights from a critical literature review”, Electronic Markets, 18(4), 345-361.
  • Cypryjański, J. & A. Grzesiuk (2016), “Herd behaviour in online auctions: A case study”, 10th European Conference on Information System Management Proceedings, The University of Evora, 45-51.
  • Daniels, K.N. & J. Vijayakumar (2007), “The impact of electronic auctions and auction types on the market for municipal bonds”, Municipal Finance Journal, 28(2), 25-47.
  • Daripa, A. & S. Kapur (2001), “Pricing on the Internet”, Oxford Review of Economic Policy, 17(2), 202-216.
  • Dasgupta, S. & R.G. Hansen (2007), “Auctions in corporate finance”, Handbook of Empirical Corporate Finance, 1, 87-143.
  • Denton, J.R. & S.L. Rev (2007), “Stacked deck: Go-Shop and auction theory”, Stanford Law Review, 60(5), 1529-1553.
  • Ethier, R. et al. (1999), “A uniform price auction with locational price adjustments for competitive electricity markets”, International Journal of Electrical Power & Energy Systems, 21(2), 103-110.
  • Etzion, O. et al. (2004), “E-CLV: a modelling approach for customer lifetime evaluation in e-commerce domains, with an application and case study for online auctions”, Information System Frontiers, 7(4-5), 421-434.
  • Flanagin, A.J. & M.J. Metzger (2007), “The role of the sites features, user attributes, and information verification behaviours on the perceived credibility of web-based information”, New Media and Society, 9(2), 319-342.
  • Ginsburgh, V. et al. (2010), “On the incidence of commissions in auction markets”, International Journal of Industrial Organization, 28(6), 639-644.
  • Graham, D. & R.C. Marshall (1987), “Collusive bidder behavior at single object second-price and English auctions,” Journal of Political Economy, 95(6), 1217-1239.
  • Gregg, D.G. & S. Walczak (2003), “E-commerce auction agents and online auction dynamics”, Electronic Markets, 13(3), 242-250.
  • Grimm, V. (2007), “An introduction to the structural econometrics of auction data”, Journal of Economics, 92(2), 205-208.
  • Guillotreau, P. & R.J. Toribio (2011), “The price effect of expanding fish auction markets”, Journal of Economic Behavior, 79(3), 211-225.
  • Güler, E. (2005), “Müzayede Teorisi, Türkiye’de Uygulaması: Telekom Örneği”, Yüksek Lisans Tezi, Uludağ Üniversitesi, Sosyal Bilimler Enstitüsü.
  • Hendricks, K. & R.H. Porter (1989), “Collusion in auctions”, Annales d’Economic et de Statisque, 15/16, 217-230.
  • Herschlag, M. & R. Zwick (2000), “Internet auctions-popular and professional literature review”, Quarterly Journal of Electronic Commerce, 1(2), 161-186.
  • Hossain, M.A. et al. (2018), “How signaling mechanisms reduce “lemons” from online group buying (OGB) markets? A study of China”, International Journal of Physical Distribution & Logistics Management, 48(7), 658-681.
  • Hou, J. & K. Elliott (2016), “Gender differences in online auctions”, Electronic Commerce Research and Applications, 17, 123-133.
  • Isaac, R.M. & C.R. Plott (1981), “Price controls and the behavior of auction markets: An experimental examination”, The American Economic Review, 71(3), 448-459.
  • İslamoğlu, A.H. (2003), Bilimsel Araştırma Yöntemleri, Literatür Yayıncılık.
  • Jafari, M. & A.A. Foroud (2020), “A medium/long-term auction-based coalition-forming model for a virtual power plant based on stochastic programming”, International Journal of Electrical Power & Energy, 118, 1-16.
  • Jiang, W. et al. (2019), “Research on the influence factors of consumer repurchase in Dutch auction”, Lecture Notes in Computer Science, 330-338.
  • Joines, J.L. et al. (2003), “Exploring motivations for consumer Web use and their implications for eCommerce”, Journal of Consumer Marketing, 20(2), 90-198.
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There are 101 citations in total.

Details

Primary Language Turkish
Subjects Economics
Journal Section Articles
Authors

Musa Türkoğlu 0000-0001-7662-9647

Gülhan Duran 0000-0002-5924-7724

Serdar Yetişen 0000-0003-3951-5805

Project Number -
Publication Date October 25, 2022
Submission Date September 17, 2021
Published in Issue Year 2022

Cite

APA Türkoğlu, M., Duran, G., & Yetişen, S. (2022). Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama. Sosyoekonomi, 30(54), 269-289. https://doi.org/10.17233/sosyoekonomi.2022.04.15
AMA Türkoğlu M, Duran G, Yetişen S. Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama. Sosyoekonomi. October 2022;30(54):269-289. doi:10.17233/sosyoekonomi.2022.04.15
Chicago Türkoğlu, Musa, Gülhan Duran, and Serdar Yetişen. “Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama”. Sosyoekonomi 30, no. 54 (October 2022): 269-89. https://doi.org/10.17233/sosyoekonomi.2022.04.15.
EndNote Türkoğlu M, Duran G, Yetişen S (October 1, 2022) Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama. Sosyoekonomi 30 54 269–289.
IEEE M. Türkoğlu, G. Duran, and S. Yetişen, “Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama”, Sosyoekonomi, vol. 30, no. 54, pp. 269–289, 2022, doi: 10.17233/sosyoekonomi.2022.04.15.
ISNAD Türkoğlu, Musa et al. “Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama”. Sosyoekonomi 30/54 (October 2022), 269-289. https://doi.org/10.17233/sosyoekonomi.2022.04.15.
JAMA Türkoğlu M, Duran G, Yetişen S. Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama. Sosyoekonomi. 2022;30:269–289.
MLA Türkoğlu, Musa et al. “Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama”. Sosyoekonomi, vol. 30, no. 54, 2022, pp. 269-8, doi:10.17233/sosyoekonomi.2022.04.15.
Vancouver Türkoğlu M, Duran G, Yetişen S. Tüketicilerin Açık Artırma Siteleri Hakkındaki Tutumlarını Belirlemeye Yönelik Bir Uygulama. Sosyoekonomi. 2022;30(54):269-8.