Research Article
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Investigation of Consumers' Attitudes towards Personalized Pricing and Dynamic Pricing Practices

Year 2023, , 243 - 256, 30.05.2023
https://doi.org/10.47097/piar.1263342

Abstract

With the developments in information technologies and shopping activities being carried out more in online environments, businesses have started to use real-time pricing mechanisms, called algorithmic pricing to increase their earnings more. In this study, it is aimed to examine the differences between consumers’ price fairness perception, price sensitivity, trust in online seller, and willingness to pay for personalized pricing and dynamic pricing applications, which are algorithmic pricing methods. For this purpose, questionnaires with two scenarios prepared for personalized pricing and dynamic pricing applications were conducted as online to two groups of participants. As a result of the data obtained in the research, it was determined that there was a statistically significant difference between the two groups in terms of consumers' willingness to pay. In line with the findings obtained as a result of the study, suggestions were made to pricing managers and academicians who will conduct research in this field.

References

  • Ackerman, C.E. (2019). What are Positive and Negative Emotions and Do We Need Both? https://positivepsychology.com/positive-negative-emotions, (Erişim: 20.11. 2022).
  • Angwin, J., & Mattioli, D. (2012). Coming Soon: Toilet Paper Price like Airline Tickets, Wall Street Journal, 5, https://www.wsj.com/articles/SB10000872396390444914904577617333130724846 (Erişim: 05.03.2023).
  • Assad, S., Clark, R., Ershov, D., & Xu, L. (2020). Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market. CESifo Working Paper, 8521, 1-77, https://dx.doi.org/10.2139/ssrn.3682021.
  • Banicevic, A., Kohlmeier, G.Z.A., Pechersky, D., & Howlett, A. (2018). Algorithms: Challenges and Opportunities for Antitrust Compliance. Aba-Sal Compliance And Ethics Committee Spotlight, Fall, 1-23.
  • Bar-Gill, O. (2019). Algorithmic Price Discrimination When Demand is a Function of Both Preferences and (Mis)perceptions. University of Chicago Law Review, 86 (2), 217-254.
  • Bar-Gill, O., Sunstein, C.R., & Talgam-Cohen, I. (2023). Algorithmic Harm in Consumer Markets. Harvard Law, Economics and Business Online, 1091, 1-65, http://www.law.harvard.edu/programs/olin_center/papers/pdf/Bar-Gill_1091.pdf (Erişim:07.03.2023).
  • Bertini, M., & Koenigsberg, O. (2021). The pitfalls of pricing algorithms: Be mindful of how they can hurt your brand. Harvard Business Review, 99(5), 74-83.
  • Biggs, C. (2019). The Sneaky (and Weird!) Thing That Can Drive up Your Amazon Prices, https://www.apartmenttherapy.com/amazon-pricing-strategy-color-264210 (Erişim: 08.03.2023).
  • Biller, S., Chan, L.M.A., Simchi-Levi, D., & Swann, J. (2005). Dynamic Pricing and the Direct-to-Customer Model in the Automotive Industry. Electronic Commerce Research, 5, 309–334, https://doi.org/10.1007/s10660-005-6161-4.
  • Boyd, D.E., & Bhat, S. (1998). The Role of Dual Entitlement and Equity Theories in Consumers' Formation of Fair Price Judgments: An Investigation Within a Business-to-Business Service Setting. Journal of Professional Services Marketing, 17(1), 1-14, https://doi.org/10.1300/J090v17n01_01.
  • Brown, Z.Y., & MacKay, A. (2021). Competition in Pricing Algorithms. Natıonal Bureau Of Economic Research, 28860, 1-64, https://doi.org/10.3386/w28860
  • Calvano, E., Calzolari, G., Denicolo, V., & Pastorello, S. (2019). Algorithmic Pricing What Implications for Competition Policy?. Review of Industrial Organization, 55(1), 155-171, https://doi.org/10.1007/s11151-019-09689-3.
  • Calvano, E., Calzolari, G., Denicolo, V., & Pastorello, S. (2020). Artificial Intelligence, Algorithmic Pricing, and Collusion. American Economic Review, 110 (10), 3267–3297, https://doi.org/10.1257/aer.20190623.
  • Cavallo, A. (2018). More Amazon Effects: Online Competition and Pricing Behaviors. National Bureau Of Economic Research, 25138, 1-37, https://doi.org/10.3386/w25138
  • Chapdelaine, P. (2020). Algorithmic Personalized Pricing. NYU Journal Of Law & Business, 17(1), 1-47, https://dx.doi.org/10.2139/ssrn.3628684
  • Chapin, A. (2016). We Can’t Figure Out Amazon’s Weird Pricing System, https://www.racked.com/2016/8/30/12692926/amazon-fashion-clothing-size-prices (Erişim: 09.03.2023).
  • Chen, L., Mislove, A., & Wilson, C. (2016). An Empirical Analysis of Algorithmic Pricing on Amazon Marketplace. WWW '16: Proceedings of the 25th International Conference , April, 11-15, https://doi.org/10.1145/2872427.2883089.
  • Cranage, D.A., & Mattila, A.S. (2006). Service Recovery and Pre-emptive Strategies for Service Failure: Both Lead to Customer Satisfaction and Loyalty, But for Different Reasons. Journal of Hospitality & Leisure Marketing, 13 (3-4), 161-181, https://doi.org/10.1300/J150v13n03_09.
  • Dai, B. (2010). The Impact of Perceived Price Fairness of Dynamic Pricing on Customer Satisfaction and Behavioral Intentions: The Moderating Role of Customer Loyalty. Auburn University, Doctoral dissertation, Alabama.
  • Dimicco, J. M., Maes, P., & Greenwald, A. (2003). Learning Curve: A Simulation-based Approach to Dynamic Pricing. Electronic Commerce Research, 3(3/4), 245-276, https://doi.org/10.1023/A:1023427023289.
  • Gautier, A., Ittoo, A., & Cleynenbreugel, P.V. (2020). AI Algorithms, Price Discrimination and Collusion: A Technological, Economic and Legal Perspective. European Journal of Law and Economics, 405-435, https://doi.org/10.1007/s10657-020-09662-6.
  • Gebhardt, G.F. (2008). Social Justice in Marketing: Fairness, Satisfaction and Customer Lifetime Value. Marketing Science Institute Special Report, January 29, 1-47.
  • Gerlick, J.A., & Liozu, S.M. (2020). Ethical and Legal Considerations of Artificial Intelligence and Algorithmic Decision-making in Personalized Pricing. Journal of Revenue and Pricing Management, 19, 85–98, https://doi.org/10.1057/s41272-019-00225-2.
  • Gordon, S.B. (2021). Can You Get a Deal After You've Paid Full Price? https://www.consumerreports.org/shopping/can-you-get-a-deal-after-you-have-paid-full-price-a9725013802/ (Erişim: 09.03.2023).
  • Harrington, J.E. (2022). The Effect of Outsourcing Pricing Algorithms on Market Competition. Management Science, 68 (9), 6355-7064, https://doi.org/10.1287/mnsc.2021.4241.
  • Herrmann, A., Xia, L., Monroe, K.B., & Huber, F. (2007). The Influence of Price Fairness on Customer Satisfaction. Journal of Product & Brand Management, 16 (1), 49–58, https://doi.org/10.1108/10610420710731151.
  • Iacobucci, D., & Duhachek, A. (2003). Advancing Alpha: Measuring Reliability with Confidence. Journal of Consumer Psychology, 13(4), 478-487, https://doi.org/10.1207/S15327663JCP1304_14.
  • Kloostra, J. (2022). Algorithmic Pricing: A Concern for Platform Workers?. European Labour Law Journal, 1–19, https://doi.org/10.1177/20319525211060360.
  • Lee,C. (2020). The Landscape of Pricing and Algorithmic Pricing. ISEAS-Yusof Ishak Institute Economics Working Paper, 6, 1-31.
  • MacKay, A.J., & Weinstein, S. N. (2022). Dynamic Pricing Algorithms, Consumer Harm, and Regulatory Response. Wash. U. L. Rev. 100, 111, 1-57.
  • Martín-Consuegra, D., Molina, A., & Esteban, Á. (2007). An Integrated Model of Price, Satisfaction and Loyalty: an Empirical Analysis in the Service Sector. Journal of Product & Brand Management, 16(7), 459-468, https://doi.org/10.1108/10610420710834913.
  • Martin, W.C., Ponder, N., & Lueg, J.E. (2009). Price Fairness Perceptions and Customer Loyalty in a Retail Context. Journal of Business Research, 62, 588–593.
  • Martin, K. (2019). Ethical Implications and Accountability of Algorithms. Journal of Business Ethics, 160, 835–850, https://doi.org/10.1007/s10551-018-3921-3
  • Maxwell, S. (2002). Rule-based Price Fairness and its Effect on Willingness to Purchase. Journal of Economic Psychology, 23, 191–212. http://dx.doi.org/10.1016/S0167-4870(02)00063-6.
  • Mehta, N., Detroja, P., & Agashe, A. (2018). Amazon Changes Prices on its Products about Every 10 Minutes—Here's How and Why They Do It. https://www.businessinsider.com/amazon-price-changes-2018-8 (Erişim: 02.03.2023).
  • Profitero Price Intelligence (2013). Amazon Makes more than 2.5 Million Daily Price Changes. https://www.profitero.com/blog/2013/12/profitero-reveals-that-amazon-com-makes-more-than-2-5-million-price-changes-every-day (Erişim: 02.03.2023).
  • Samuel, L.H.S., Balaji, M.S., & Wei, K.K. (2015) An Investigation of Online Shopping Experience on Trust and Behavioral Intentions, Journal of Internet Commerce, 14:2, 233-254, https://doi.org/10.1080/15332861.2015.1028250.
  • Seele, P., Dierksmeier, C., Hofstetter, R., & Schultz, M.D. (2021). Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing. Journal of Business Ethics, 170, 697–719, https://doi.org/10.1007/s10551-019-04371-w.
  • Seçer, İ. (2015). SPSS ve LISREL ile Pratik Veri Analizi, 2. Baskı, Ankara: Anı Yayıncılık.
  • Stobierski, T. (2020). Willingness To Pay: What It Is & How To Calculate, https://online.hbs.edu/blog/post/willingness-to-pay (Erişim: 08.03.2023).
  • Tabachnick, B.G. & Fidell. L.S. (2019). Using Multivariate Statistics, Seventh Ed., New York: Pearson.
  • Tulwin, K. (2014). The Influence of Price Changes on Consumers’ Purchase Decisions. Nova School of Business and Economics, Master Thesis, Portugal.
  • Urban, G. L., Sultan F., & Qualls, W. (2000). Placing Trust at the Center of Your Internet Strategy. Sloan Management Review, 39-48.
  • Urbany, J.E., Madden, T.J., & Dickson, P.R.(1989). All's not Fair in Pricing: An Initial Look at the Dual Entitlement Principle. Market Letters, 1, 17-25, https://doi.org/10.1007/BF00436145.
  • Victor, V., Thoppan, J.J., Fekete-Farkas, M., & Grabara, J. (2019). Pricing Strategies in the Era of Digitalisation and the Perceived Shift in Consumer Behaviour of Youth in Poland. Journal of International Studies, 12(3), 74-91, https://doi.org/10.14254/2071-8330.2019/12-3/7.
  • Vomberg, A. (2021). Pricing in the Digital Age: A Roadmap to Becoming a Dynamic Pricing Retailer. Holland: University of Groningen Press. 
  • Wakefield, K.L., & Inman, J.J. (2003). Situational Price Sensitivity: The Role of Consumption Occasion, Social Context and Income. Journal of Retailing, 79, 199–212, https://doi.org/10.1016/j.jretai.2003.09.004.
  • Wieting, M., & Sapi, G. (2021). Algorithms in the Marketplace: An Empirical Analysis of Automated Pricing in E-Commerce. NET Institute, 21-06, 1-58, https://dx.doi.org/10.2139/ssrn.3945137.
  • Xia, L., Monroe, K.B., & Cox, J.L. (2004). The Price is Unfair! A Conceptual Framework of Price Fairness Perceptions. Journal of Marketing, 68(10), 1–15, https://doi.org/10.1509/jmkg.68.4.1.42733.
  • Xu, Q. (2021). The Impact of Online Dynamic Pricing Strategies on Consumers’ Trust, Fairness Perceptions, and Loyalty, MODUL University, Master Thesis, Vienna.
  • Zuiderveen Borgesius, F., & Poort, J. (2017). Online Price Discrimination and EU Data Privacy Law. Journal of Consumer Policy, 40(3), 347–366, https://doi.org/10.1007/s10603-017-9354-z.

Tüketicilerin Kişiselleştirilmiş Fiyatlandırma ile Dinamik Fiyatlandırma Uygulamalarına Yönelik Tutumlarının İncelenmesi

Year 2023, , 243 - 256, 30.05.2023
https://doi.org/10.47097/piar.1263342

Abstract

Bilgi teknolojilerindeki gelişmeler ve alışveriş faaliyetlerinin çevrimiçi ortamlarda daha fazla gerçekleştirilmesiyle birlikte, işletmeler, kazançlarını daha fazla artırmak amacıyla algoritmik fiyatlandırma olarak adlandırılan gerçek zamanlı fiyatlandırma mekanizmalarını kullanmaya başlamışlardır. Bu çalışmada algoritmik fiyatlandırma yöntemleri olan kişiselleştirilmiş fiyatlandırma ile dinamik fiyatlandırma uygulamalarına yönelik olarak tüketicilerin fiyat adaleti algısı, fiyat duyarlılığı, çevrim içi satıcıya duyulan güven ve ödeme istekliliği arasındaki farklılıklarının incelenmesi amaçlanmıştır. Bu amaç doğrultusunda kişiselleştirilmiş fiyatlandırma ile dinamik fiyatlandırma uygulamalarına yönelik hazırlanan iki senaryonun bulunduğu anketler iki gruba çevrimiçi olarak uygulanmıştır. Araştırmada elde edilen veriler sonucunda, tüketicilerin ödeme isteklilikleri bakımından iki grup arasında istatistiksel olarak anlamlı farklılığın bulunduğu belirlenmiştir. Çalışmanın sonucunda elde edilen bulgular doğrultusunda, fiyatlandırma yöneticilerine ve bu alanda araştırma yapacak olan akademisyenlere önerilerde bulunulmuştur.

References

  • Ackerman, C.E. (2019). What are Positive and Negative Emotions and Do We Need Both? https://positivepsychology.com/positive-negative-emotions, (Erişim: 20.11. 2022).
  • Angwin, J., & Mattioli, D. (2012). Coming Soon: Toilet Paper Price like Airline Tickets, Wall Street Journal, 5, https://www.wsj.com/articles/SB10000872396390444914904577617333130724846 (Erişim: 05.03.2023).
  • Assad, S., Clark, R., Ershov, D., & Xu, L. (2020). Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market. CESifo Working Paper, 8521, 1-77, https://dx.doi.org/10.2139/ssrn.3682021.
  • Banicevic, A., Kohlmeier, G.Z.A., Pechersky, D., & Howlett, A. (2018). Algorithms: Challenges and Opportunities for Antitrust Compliance. Aba-Sal Compliance And Ethics Committee Spotlight, Fall, 1-23.
  • Bar-Gill, O. (2019). Algorithmic Price Discrimination When Demand is a Function of Both Preferences and (Mis)perceptions. University of Chicago Law Review, 86 (2), 217-254.
  • Bar-Gill, O., Sunstein, C.R., & Talgam-Cohen, I. (2023). Algorithmic Harm in Consumer Markets. Harvard Law, Economics and Business Online, 1091, 1-65, http://www.law.harvard.edu/programs/olin_center/papers/pdf/Bar-Gill_1091.pdf (Erişim:07.03.2023).
  • Bertini, M., & Koenigsberg, O. (2021). The pitfalls of pricing algorithms: Be mindful of how they can hurt your brand. Harvard Business Review, 99(5), 74-83.
  • Biggs, C. (2019). The Sneaky (and Weird!) Thing That Can Drive up Your Amazon Prices, https://www.apartmenttherapy.com/amazon-pricing-strategy-color-264210 (Erişim: 08.03.2023).
  • Biller, S., Chan, L.M.A., Simchi-Levi, D., & Swann, J. (2005). Dynamic Pricing and the Direct-to-Customer Model in the Automotive Industry. Electronic Commerce Research, 5, 309–334, https://doi.org/10.1007/s10660-005-6161-4.
  • Boyd, D.E., & Bhat, S. (1998). The Role of Dual Entitlement and Equity Theories in Consumers' Formation of Fair Price Judgments: An Investigation Within a Business-to-Business Service Setting. Journal of Professional Services Marketing, 17(1), 1-14, https://doi.org/10.1300/J090v17n01_01.
  • Brown, Z.Y., & MacKay, A. (2021). Competition in Pricing Algorithms. Natıonal Bureau Of Economic Research, 28860, 1-64, https://doi.org/10.3386/w28860
  • Calvano, E., Calzolari, G., Denicolo, V., & Pastorello, S. (2019). Algorithmic Pricing What Implications for Competition Policy?. Review of Industrial Organization, 55(1), 155-171, https://doi.org/10.1007/s11151-019-09689-3.
  • Calvano, E., Calzolari, G., Denicolo, V., & Pastorello, S. (2020). Artificial Intelligence, Algorithmic Pricing, and Collusion. American Economic Review, 110 (10), 3267–3297, https://doi.org/10.1257/aer.20190623.
  • Cavallo, A. (2018). More Amazon Effects: Online Competition and Pricing Behaviors. National Bureau Of Economic Research, 25138, 1-37, https://doi.org/10.3386/w25138
  • Chapdelaine, P. (2020). Algorithmic Personalized Pricing. NYU Journal Of Law & Business, 17(1), 1-47, https://dx.doi.org/10.2139/ssrn.3628684
  • Chapin, A. (2016). We Can’t Figure Out Amazon’s Weird Pricing System, https://www.racked.com/2016/8/30/12692926/amazon-fashion-clothing-size-prices (Erişim: 09.03.2023).
  • Chen, L., Mislove, A., & Wilson, C. (2016). An Empirical Analysis of Algorithmic Pricing on Amazon Marketplace. WWW '16: Proceedings of the 25th International Conference , April, 11-15, https://doi.org/10.1145/2872427.2883089.
  • Cranage, D.A., & Mattila, A.S. (2006). Service Recovery and Pre-emptive Strategies for Service Failure: Both Lead to Customer Satisfaction and Loyalty, But for Different Reasons. Journal of Hospitality & Leisure Marketing, 13 (3-4), 161-181, https://doi.org/10.1300/J150v13n03_09.
  • Dai, B. (2010). The Impact of Perceived Price Fairness of Dynamic Pricing on Customer Satisfaction and Behavioral Intentions: The Moderating Role of Customer Loyalty. Auburn University, Doctoral dissertation, Alabama.
  • Dimicco, J. M., Maes, P., & Greenwald, A. (2003). Learning Curve: A Simulation-based Approach to Dynamic Pricing. Electronic Commerce Research, 3(3/4), 245-276, https://doi.org/10.1023/A:1023427023289.
  • Gautier, A., Ittoo, A., & Cleynenbreugel, P.V. (2020). AI Algorithms, Price Discrimination and Collusion: A Technological, Economic and Legal Perspective. European Journal of Law and Economics, 405-435, https://doi.org/10.1007/s10657-020-09662-6.
  • Gebhardt, G.F. (2008). Social Justice in Marketing: Fairness, Satisfaction and Customer Lifetime Value. Marketing Science Institute Special Report, January 29, 1-47.
  • Gerlick, J.A., & Liozu, S.M. (2020). Ethical and Legal Considerations of Artificial Intelligence and Algorithmic Decision-making in Personalized Pricing. Journal of Revenue and Pricing Management, 19, 85–98, https://doi.org/10.1057/s41272-019-00225-2.
  • Gordon, S.B. (2021). Can You Get a Deal After You've Paid Full Price? https://www.consumerreports.org/shopping/can-you-get-a-deal-after-you-have-paid-full-price-a9725013802/ (Erişim: 09.03.2023).
  • Harrington, J.E. (2022). The Effect of Outsourcing Pricing Algorithms on Market Competition. Management Science, 68 (9), 6355-7064, https://doi.org/10.1287/mnsc.2021.4241.
  • Herrmann, A., Xia, L., Monroe, K.B., & Huber, F. (2007). The Influence of Price Fairness on Customer Satisfaction. Journal of Product & Brand Management, 16 (1), 49–58, https://doi.org/10.1108/10610420710731151.
  • Iacobucci, D., & Duhachek, A. (2003). Advancing Alpha: Measuring Reliability with Confidence. Journal of Consumer Psychology, 13(4), 478-487, https://doi.org/10.1207/S15327663JCP1304_14.
  • Kloostra, J. (2022). Algorithmic Pricing: A Concern for Platform Workers?. European Labour Law Journal, 1–19, https://doi.org/10.1177/20319525211060360.
  • Lee,C. (2020). The Landscape of Pricing and Algorithmic Pricing. ISEAS-Yusof Ishak Institute Economics Working Paper, 6, 1-31.
  • MacKay, A.J., & Weinstein, S. N. (2022). Dynamic Pricing Algorithms, Consumer Harm, and Regulatory Response. Wash. U. L. Rev. 100, 111, 1-57.
  • Martín-Consuegra, D., Molina, A., & Esteban, Á. (2007). An Integrated Model of Price, Satisfaction and Loyalty: an Empirical Analysis in the Service Sector. Journal of Product & Brand Management, 16(7), 459-468, https://doi.org/10.1108/10610420710834913.
  • Martin, W.C., Ponder, N., & Lueg, J.E. (2009). Price Fairness Perceptions and Customer Loyalty in a Retail Context. Journal of Business Research, 62, 588–593.
  • Martin, K. (2019). Ethical Implications and Accountability of Algorithms. Journal of Business Ethics, 160, 835–850, https://doi.org/10.1007/s10551-018-3921-3
  • Maxwell, S. (2002). Rule-based Price Fairness and its Effect on Willingness to Purchase. Journal of Economic Psychology, 23, 191–212. http://dx.doi.org/10.1016/S0167-4870(02)00063-6.
  • Mehta, N., Detroja, P., & Agashe, A. (2018). Amazon Changes Prices on its Products about Every 10 Minutes—Here's How and Why They Do It. https://www.businessinsider.com/amazon-price-changes-2018-8 (Erişim: 02.03.2023).
  • Profitero Price Intelligence (2013). Amazon Makes more than 2.5 Million Daily Price Changes. https://www.profitero.com/blog/2013/12/profitero-reveals-that-amazon-com-makes-more-than-2-5-million-price-changes-every-day (Erişim: 02.03.2023).
  • Samuel, L.H.S., Balaji, M.S., & Wei, K.K. (2015) An Investigation of Online Shopping Experience on Trust and Behavioral Intentions, Journal of Internet Commerce, 14:2, 233-254, https://doi.org/10.1080/15332861.2015.1028250.
  • Seele, P., Dierksmeier, C., Hofstetter, R., & Schultz, M.D. (2021). Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing. Journal of Business Ethics, 170, 697–719, https://doi.org/10.1007/s10551-019-04371-w.
  • Seçer, İ. (2015). SPSS ve LISREL ile Pratik Veri Analizi, 2. Baskı, Ankara: Anı Yayıncılık.
  • Stobierski, T. (2020). Willingness To Pay: What It Is & How To Calculate, https://online.hbs.edu/blog/post/willingness-to-pay (Erişim: 08.03.2023).
  • Tabachnick, B.G. & Fidell. L.S. (2019). Using Multivariate Statistics, Seventh Ed., New York: Pearson.
  • Tulwin, K. (2014). The Influence of Price Changes on Consumers’ Purchase Decisions. Nova School of Business and Economics, Master Thesis, Portugal.
  • Urban, G. L., Sultan F., & Qualls, W. (2000). Placing Trust at the Center of Your Internet Strategy. Sloan Management Review, 39-48.
  • Urbany, J.E., Madden, T.J., & Dickson, P.R.(1989). All's not Fair in Pricing: An Initial Look at the Dual Entitlement Principle. Market Letters, 1, 17-25, https://doi.org/10.1007/BF00436145.
  • Victor, V., Thoppan, J.J., Fekete-Farkas, M., & Grabara, J. (2019). Pricing Strategies in the Era of Digitalisation and the Perceived Shift in Consumer Behaviour of Youth in Poland. Journal of International Studies, 12(3), 74-91, https://doi.org/10.14254/2071-8330.2019/12-3/7.
  • Vomberg, A. (2021). Pricing in the Digital Age: A Roadmap to Becoming a Dynamic Pricing Retailer. Holland: University of Groningen Press. 
  • Wakefield, K.L., & Inman, J.J. (2003). Situational Price Sensitivity: The Role of Consumption Occasion, Social Context and Income. Journal of Retailing, 79, 199–212, https://doi.org/10.1016/j.jretai.2003.09.004.
  • Wieting, M., & Sapi, G. (2021). Algorithms in the Marketplace: An Empirical Analysis of Automated Pricing in E-Commerce. NET Institute, 21-06, 1-58, https://dx.doi.org/10.2139/ssrn.3945137.
  • Xia, L., Monroe, K.B., & Cox, J.L. (2004). The Price is Unfair! A Conceptual Framework of Price Fairness Perceptions. Journal of Marketing, 68(10), 1–15, https://doi.org/10.1509/jmkg.68.4.1.42733.
  • Xu, Q. (2021). The Impact of Online Dynamic Pricing Strategies on Consumers’ Trust, Fairness Perceptions, and Loyalty, MODUL University, Master Thesis, Vienna.
  • Zuiderveen Borgesius, F., & Poort, J. (2017). Online Price Discrimination and EU Data Privacy Law. Journal of Consumer Policy, 40(3), 347–366, https://doi.org/10.1007/s10603-017-9354-z.
There are 51 citations in total.

Details

Primary Language Turkish
Subjects Business Administration
Journal Section Research Articles
Authors

Gizem Aydan 0000-0002-8548-1979

Kalender Özcan Atılgan 0000-0003-1482-4505

Publication Date May 30, 2023
Published in Issue Year 2023

Cite

APA Aydan, G., & Atılgan, K. Ö. (2023). Tüketicilerin Kişiselleştirilmiş Fiyatlandırma ile Dinamik Fiyatlandırma Uygulamalarına Yönelik Tutumlarının İncelenmesi. Pamukkale Üniversitesi İşletme Araştırmaları Dergisi, 10(1-Prof. Dr. Feyzullah EROĞLU Armağan Sayısı), 243-256. https://doi.org/10.47097/piar.1263342

Pamukkale Üniversitesi İşletme Araştırmaları Dergisinde yayınlanmış makalelerin telif hakları Creative Commons Atıf-Gayriticari 4.0 Uluslararası Lisansı (CC BY-NC-ND 4.0) kapsamındadır.

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