Provide a pattern for choosing a discount-based pricing strategy in marketing (Case Study in a Chain Store)

Document Type : Original Article

Authors

School of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

Perceived value is a parameter affecting customer satisfaction and customer retention rate. Pricing as a revenue factor in the marketing mix among other factors of product, location and promotion has a significant impact on the customer perceived value. Customer mentality of pre-purchase pricing can affect his future behavior. Choosing the right pricing and discounting strategy and using the appropriate sales and marketing tactics is effective in retaining and returning customers. Choosing the right pricing strategy can be influenced by many factors such as product brand, type of customers, geographical area, pricing and discount policies, the vision of the company and etc. In this paper, we try to examine the perceived value functions in marketing and select appropriate criteria with the aim of maximizing the perceived value of stakeholders and using MCDM decision methods and DEMATEL causal approach to selecting the best discount pricing strategy in Marketing is addressed by a case study of a specific chain store. The results showed that the two anchoring pricing and discount pricing strategies were obtained using two methods of network analysis approach and laboratory evaluation and decision testing as the two best methods for the store. The results of VIKOR model solution also consider the pricing strategy based on the product portfolio as the first priority proposed to the sales and marketing managers of the store.

Keywords


  1. Segarra-Moliner JR, Moliner-Tena MÁ. Customer equity and CLV in Spanish telecommunication services. J Bus Res [Internet]. 2016;69(10):4694–705. Available from: http://dx.doi.org/10.1016/j.jbusres.2016.04.017.
  2. Zhou L, Gupta SM. Marketing research and life cycle pricing strategies for new and remanufactured products. J Remanufacturing. 2019 Apr 28;9(1):29–50.
  3. Giri RN, Mondal SK, Maiti M. Bundle pricing strategies for two complementary products with different channel powers. Ann Oper Res [Internet]. 2020 Apr 28;287(2):701–25. Available from: http://link.springer.com/10.1007/s10479-017-2632-y.
  4. Kienzler M, Kowalkowski C. Pricing strategy: A review of 22 years of marketing research. J Bus Res. 2017;78(May):101–10.
  5. Dahana WD, Miwa Y, Morisada M. Linking lifestyle to customer lifetime value: An exploratory study in an online fashion retail market. J Bus Res [Internet]. 2019;99(December 2017):319–31. Available from: https://doi.org/10.1016/j.jbusres.2019.02.049
  6. Jain R, Aagja J, Bagdare S. Customer experience – a review and research agenda. J Serv Theory Pract. 2017;27(3):642–62.
  7. El-Adly MI. Modelling the relationship between hotel perceived value, customer satisfaction, and customer loyalty. J Retail Consum Serv. 2019;50:322–32.
  8. کتابی س, انصاری م, ناصری طاهری م. انتخاب آمیخته بازاریابی مناسب با استفاده از تکنیک Ahp با رویکرد برنامه ریزی استراتژیک بازاریابی(مطالعه موردی: شرکت کاشی مرجان). Vol. 1, مجله دانشکده علوم اداری و اقتصادی دانشگاه اصفهان. 1384.
  9. Kotler P, Keller kevin lane. Marketing Management (15th Edition) 2016 - Kotler & Keller [Dr.Soc].pdf. 2015. p. 497.
  10. Sadeghpour F, Far MG, Khah AR, Akbardokht Amiri MA. Marketing Strategic Planning and Choosing the Right Strategy using AHP Technique (Case Study: Ghavamin Bank Mazandaran). Vol. 1, Dutch Journal of Finance and Management. 2019.
  11. Publications SA, Bonyani A, Namamian F. Determining the Relationship Between the Shopping Center Environment with Customer-Perceived Value , Customer Satisfaction , And Loyalty. 2017;3(3):52–9.
  12. استادی ب, عبدالهی ع. ارائه یک فرمول ریاضی جدید برای محاسبه ارزش درک شده مشتریان با استفاده از تابع زیان تاگوچی و مفهوم ارزش دوره عمر مشتری. تحقیقات بازاریابی نوین [Internet]. 2020; Available from: https://nmrj.ui.ac.ir/article_25003.html
  13. Liu Y, Eckert CM, Earl C. A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Syst Appl [Internet]. 2020 Dec;161:113738. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0957417420305625
  14. Miciuła I, Nowakowska-Grunt J. Using the AHP method to select an energy supplier for household in Poland. Procedia Comput Sci [Internet]. 2019;159:2324–34. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1877050919316114
  15. Liang D, Dai Z, Wang M. Assessing customer satisfaction of O2O takeaway based on online reviews by integrating fuzzy comprehensive evaluation with AHP and probabilistic linguistic term sets. Applied Soft Computing Journal. 2020.
  16. McLean G, Wilson A. Shopping in the digital world: Examining customer engagement through augmented reality mobile applications. Comput Human Behav [Internet]. 2019;101(November 2018):210–24. Available from: https://doi.org/10.1016/j.chb.2019.07.002
  17. Haque HME, Dhakal S, Mostafa SMG. An assessment of opportunities and challenges for cross-border electricity trade for Bangladesh using SWOT-AHP approach. Vol. 137, Energy Policy. 2020.
  18. Yıldız N, Tüysüz F. A hybrid multi-criteria decision making approach for strategic retail location investment: Application to Turkish food retailing. Socioecon Plann Sci [Internet]. 2019 Dec;68:100619. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0038012117300526
  19. Olczak M. Chain-Store Pricing and the Structure of Retail Markets. J Ind Compet Trade. 2015;15(2):87–104.
  20. Álvarez-Rodríguez C, Martín-Gamboa M, Iribarren D. Sensitivity of operational and environmental benchmarks of retail stores to decision-makers’ preferences through Data Envelopment Analysis. Sci Total Environ [Internet]. 2020 May;718:137330. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0048969720308408
  21. del Rio Olivares MJ, Wittkowski K, Aspara J, Falk T, Mattila P. Relational Price Discounts: Consumers’ Metacognitions and Nonlinear Effects of Initial Discounts on Customer Retention. J Mark [Internet]. 2018 Jan;82(1):115–31. Available from: http://journals.sagepub.com/doi/10.1509/jm.16.0267
  22. CHUNG YOUN KYAEI, Lee,Sang-Suk. A Study on Development Strategy of Korean Hidden Champion Firm Utilizing the SWOT/AHP Technique. Vol. 8, Asia-Pacific Journal of Business Venturing and Entrepreneurship. 2013. p. 97–111.
  23. Lim LG, Tuli KR, Grewal R. Customer Satisfaction and Its Impact on the Future Costs of Selling. J Mark [Internet]. 2020 Jul 15;84(4):23–44. Available from: http://journals.sagepub.com/doi/10.1177/0022242920923307
  24. Cai Q, Luo C, Tian X, Wang S. Uniform Pricing Strategy vs. Price Differentiation Strategy in the Presence of Cost Saving and Demand Increasing. J Syst Sci Complex [Internet]. 2019 Jun 17;32(3):932–46. Available from: http://link.springer.com/10.1007/s11424-019-7082-y
  25. Fecher A, Robbert T, Roth S. Unit Price Measures in Retailing: Consistency Effects on Product Choice and Store Evaluations. J Consum Policy [Internet]. 2020 Sep 15;43(3):611–33. Available from: http://link.springer.com/10.1007/s10603-020-09456-y
  26. صمدی م, فاخر ا. برنامه ریزی استراتژیک بازاریابی و انتخاب استراتژی مناسب با استفاده از تکنیک AHP (شرکت لوله سازی اهواز). دانشور رفتار [Internet]. 1388;16(35 (ویژه مقالات مدیریت 12)):69–82.

Available from:

https://www.sid.ir/fa/journal/ViewPaper.aspx?ID=122384

  1. Esmaeiligookeh M, Tarokh MJ. Customer Lifetime Value Models : A literature Survey. 2011;
  2. Danziger S, Hadar L, Morwitz VG. Retailer Pricing Strategy and Consumer Choice under Price Uncertainty. J Consum Res [Internet]. 2014 Oct 1;41(3):761–74. Available from: https://academic.oup.com/jcr/article-lookup/doi/10.1086/677313
  3. Ellickson PB, Misra S. Supermarket Pricing Strategies. Mark Sci. 2008;27(5):811–28.
  4. حمیدی ن, راه چمنی ا, مرتضوی س. اولویت بندی راهبرد ها در تجارت الکترونیکی (در سایت های تخفیف اینترنتی در ایران). راهبردهای بازرگانی

[Internet]. 1393;21(3):11–24. Available from: https://www.sid.ir/fa/journal/ViewPaper.aspx?id=251643

  1. Torbacki W, Kijewska K. ScienceDirect ScienceDirect Identifying Key Performance Indicators to be used in Logistics 4 . 0 Identifying Key Performance Indicators to be used in Logistics 4 . 0 and Industry 4 . 0 for the needs of sustainable municipal logistics by and Industry 4 . 0 [Internet]. Vol. 39, Transportation Research Procedia. 2019. p. 534–43. Available from:

     https://doi.org/10.1016/j.trpro.2019.06.055

  1. Tan T, Mills G, Papadonikolaki E, Liu Z. Combining multi-criteria decision making (MCDM) methods with building information modelling (BIM): A review. Autom Constr [Internet]. 2021 Jan;121:103451. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0926580520310311