Development of an integrated discounting strategy based on vendors’ expectations using FAHP and fuzzy goal programming
Abstract
The main goal of a company is to increase its market share and total profits at the same time. However, these two objectives conflict if discount rates are applied to vendors. The objective of this paper is to develop an integrated discounting strategy method to effectively manage the transactions of the vendors by determining the optimum discount rates which balance the increase on the market share and the total profit. With the proposed methodology which utilizes fuzzy analytic hierarchy process and fuzzy goal programming, determination of the discount rates of each vendor under different discounting strategies is facilitated. This enables the vendors to choose the most suitable discounting strategy with the best applicable discount rate and enables the managers to predict the transactions of the vendors. The proposed method is validated with a numerical study conducted on a pilot region of an international company.
First published online: 07 Mar 2017
Keyword : discounting strategy, fuzzy goal programming, fuzzy analytic hierarchy process, revenue management, risk management, supply chain management
How to Cite
Ucal Sari, I. (2018). Development of an integrated discounting strategy based on vendors’ expectations using FAHP and fuzzy goal programming. Technological and Economic Development of Economy, 24(2), 635–652. https://doi.org/10.3846/20294913.2016.1213205
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Harries, C.; Yaniv, I.; Harvey, N. 2004. Combining advice: the weight of a dissenting opinion in the consensus, Journal of Behavioral Decision Making 17(5): 333–348. https://doi.org/10.1002/bdm.474
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Kahraman, C.; Cebeci, U.; Ulukan, Z. 2003. Multi-criteria supplier selection using fuzzy AHP, Logistics Information Management 16(6): 382–394. https://doi.org/10.1108/09576050310503367
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Shaw, K.; Shankar, R.; Yadav, S. S.; Thakur, L. S. 2012. Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain, Expert Systems with Applications 39(9): 8182–8192. https://doi.org/10.1016/j.eswa.2012.01.149
Sinha, S.; Sarmah, S. P. 2010a. Single-vendor multi-buyer discount pricing model: an evolutionary com¬putation-based approach, International Journal of Operational Research 8(1): 1–19. https://doi.org/10.1504/IJOR.2010.033101
Sinha, S.; Sarmah, S. P. 2010b. Single-vendor multi-buyer discount pricing model under stochastic demand environment, Computers & Industrial Engineering 59(4): 945–953. https://doi.org/10.1016/j.cie.2010.09.005
Tam, M. C.; Tummala, V. R. 2001. An application of the AHP in vendor selection of a telecommunications system, Omega 29(2): 171–182. https://doi.org/10.1016/S0305–0483(00)00039–6
Van Laarhoven, P. J. M.; Pedrycz, W. 1983. A fuzzy extension of Saaty’s priority theory, Fuzzy Sets and Systems 11(1): 199–227. https://doi.org/10.1016/s0165–0114(83)80082–7
Viswanathan, S.; Wang, Q. 2003. Discount pricing decisions in distribution channels with price-sensitive demand, European Journal of Operational Research 149(3): 571–587. https://doi.org/10.1016/S0377–2217(02)00469–1
Wadhwa, V.; Ravindran, A. R. 2007. Vendor selection in outsourcing, Computers and Operations Research 34(12): 3725–3737. https://doi.org/10.1016/j.cor.2006.01.009
Wang, T. Y.; Yang, Y. H. 2009. A fuzzy model for supplier selection in quantity discount environments, Expert Systems with Applications 36(10): 12179–12187. https://doi.org/10.1016/j.eswa.2009.03.018
Wang, Z.; Hu, M. 2014. Committed versus contingent pricing under competition, Production and Operations Management 23(11): 1919–1936. https://doi.org/10.1111/poms.12202
Weber, C. A.; Current, J. R.; Benton, W. C. 1991. Vendor selection criteria and methods, European Journal of Operational Research 50(1): 2–18. https://doi.org/10.1016/0377–2217(91)90033-R
Yahya, S.; Kingsman, B. 1999. Vendor rating for an entrepreneur development programme: a case study using the analytic hierarchy process method, Journal of the Operational Research Society 50(9): 916–930. https://doi.org/10.1057/palgrave.jors.2600797
Yang, J. L.; Chiu, H. N.; Tzeng, G. H.; Yeh, R. H. 2008. Vendor selection by integrated fuzzy MCDM techniques with independent and interdependent relationships, Information Sciences 178(21): 4166–4183. https://doi.org/10.1016/j.ins.2008.06.003
Yin, M.; Kim, K. H. 2012. Quantity discount pricing for container transportation services by shipping lines, Computers and Industrial Engineering 63(1): 313–322. https://doi.org/10.1016/j.cie.2012.03.008
Zeng, J.; An, M.; Smith, N. J. 2007. Application of a fuzzy based decision making methodology to construction project risk assessment, International Journal of Project Management 25(6): 589–600. https://doi.org/10.1016/j.ijproman.2007.02.006
Braide, S.; Cao, Z.; Zeng, X. 2012. Volume discount pricing strategy in the VMI supply chain with price sensitive demand, Journal of the Operational Research Society 64(6): 833–847. https://doi.org/10.1057/jors.2012.85
Buckley, J. J. 1985. Fuzzy hierarchical analysis, Fuzzy sets and systems 17(3): 233–247. https://doi.org/10.1016/0165–0114(85)90090–9
Cheng, Y. 2013. Research on dynamic pricing based on rationing for two deterministic demand classes, Chapter 45, in W. Du (Ed.). Lecture notes in electrical engineering 207 LNEE. London: Springer-Verlag. https://doi.org/10.1007/978–1-4471–4793–0_45
Chung, J.; Li, D. 2013. The prospective impact of a multi-period pricing strategy on consumer perceptions for perishable foods, British Food Journal 115(3): 377–393. https://doi.org/10.1108/00070701311314200
Croes, R. R.; Semrad, K. J.; Yost, E. 2010. Explaining the pricing decision-making process in the hotel industry, Chapter 4 in P. M. Berge, S. B. Eliassen (Eds). Hospitality and Tourism Management. New York: Nova Science Publishers.
Ertuğrul, İ.; Karakaşoğlu, N. 2009. Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods, Expert Systems with Applications 36(1): 702–715. https://doi.org/10.1016/j.eswa.2007.10.014
Galankashi, M. R.; Chegeni, A.; Soleimanynanadegany, A.; Memari, A.; Anjomshoae, A.; Helmi, S. A.; Dargi, A. 2015. Prioritizing green supplier selection criteria using fuzzy analytical network process, Procedia CIRP 26: 689–694. https://doi.org/10.1016/j.procir.2014.07.044
Hannan, E. L. 1981. Linear programming with multiple fuzzy goals, Fuzzy Sets and Systems 6: 235–248. https://doi.org/10.1016/0165–0114(81)90002–6
Haq, A. N.; Kannan, G. 2006. Fuzzy analytical hierarchy process for evaluating and selecting a vendor in a supply chain model, The International Journal of Advanced Manufacturing Technology 29(7–8): 826–835.
Harries, C.; Yaniv, I.; Harvey, N. 2004. Combining advice: the weight of a dissenting opinion in the consensus, Journal of Behavioral Decision Making 17(5): 333–348. https://doi.org/10.1002/bdm.474
Hsieh, C.-C.; Liu, Y.-T.; Wang, W.-M. 2010. Coordinating ordering and pricing decisions in a two-stage distribution system with price-sensitive demand through short-term discounting, European Journal of Operational Research 207(1): 142–151. https://doi.org/10.1016/j.ejor.2010.03.035
Hsieh, T. Y.; Lu, S. T.; Tzeng, G. H. 2004. Fuzzy MCDM approach for planning and design tenders selection in public office buildings, International Journal of Project Management 22(7): 573–584. https://doi.org/10.1016/j.ijproman.2004.01.002
Jakhar, S. K. 2015. Performance evaluation and a flow allocation decision model for a sustainable supply chain of an apparel industry, Journal of Cleaner Production 87: 391–413. https://doi.org/10.1016/j.jclepro.2014.09.089
Kahraman, C.; Cebeci, U.; Ulukan, Z. 2003. Multi-criteria supplier selection using fuzzy AHP, Logistics Information Management 16(6): 382–394. https://doi.org/10.1108/09576050310503367
Kamali, A.; Ghomi, S. F.; Jolai, F. 2011. A multi-objective quantity discount and joint optimization model for coordination of a single-buyer multi-vendor supply chain, Computers and Mathematics with Applications 62(8): 3251–3269. https://doi.org/10.1016/j.camwa.2011.08.040
Kar, A. K. 2014. Revisiting the supplier selection problem: an integrated approach for group decision sup¬port, Expert Systems with Applications 41(6): 2762–2771. https://doi.org/10.1016/j.eswa.2013.10.009
Kilincci, O.; Onal, S. A. 2011. Fuzzy AHP approach for supplier selection in a washing machine company, Expert Systems with Applications 38(8): 9656–9664. https://doi.org/10.1016/j.eswa.2011.01.159
Kumar, A. 2016. A conceptual model for automation of product dynamic pricing and sales promotion for a retail organization, Kybernetes 45(3): 490–507. https://doi.org/10.1108/K-03–2015–0075
Kumar, M.; Vrat, P.; Shankar, R. 2004. A fuzzy goal programming approach for vendor selection problem in a supply chain, Computers and Industrial Engineering 46(1): 69–85. https://doi.org/10.1016/j.cie.2003.09.010
Senvar, M. O.; Vayvay, O.; Kurt, E.; Hloch, S. 2014. Prioritization of balanced scorecard measurement indicators as a process management approach via fuzzy AHP: case study in automotive industry, Tehnicki Vjesnik 21(1): 155–162.
Shaw, K.; Shankar, R.; Yadav, S. S.; Thakur, L. S. 2012. Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain, Expert Systems with Applications 39(9): 8182–8192. https://doi.org/10.1016/j.eswa.2012.01.149
Sinha, S.; Sarmah, S. P. 2010a. Single-vendor multi-buyer discount pricing model: an evolutionary com¬putation-based approach, International Journal of Operational Research 8(1): 1–19. https://doi.org/10.1504/IJOR.2010.033101
Sinha, S.; Sarmah, S. P. 2010b. Single-vendor multi-buyer discount pricing model under stochastic demand environment, Computers & Industrial Engineering 59(4): 945–953. https://doi.org/10.1016/j.cie.2010.09.005
Tam, M. C.; Tummala, V. R. 2001. An application of the AHP in vendor selection of a telecommunications system, Omega 29(2): 171–182. https://doi.org/10.1016/S0305–0483(00)00039–6
Van Laarhoven, P. J. M.; Pedrycz, W. 1983. A fuzzy extension of Saaty’s priority theory, Fuzzy Sets and Systems 11(1): 199–227. https://doi.org/10.1016/s0165–0114(83)80082–7
Viswanathan, S.; Wang, Q. 2003. Discount pricing decisions in distribution channels with price-sensitive demand, European Journal of Operational Research 149(3): 571–587. https://doi.org/10.1016/S0377–2217(02)00469–1
Wadhwa, V.; Ravindran, A. R. 2007. Vendor selection in outsourcing, Computers and Operations Research 34(12): 3725–3737. https://doi.org/10.1016/j.cor.2006.01.009
Wang, T. Y.; Yang, Y. H. 2009. A fuzzy model for supplier selection in quantity discount environments, Expert Systems with Applications 36(10): 12179–12187. https://doi.org/10.1016/j.eswa.2009.03.018
Wang, Z.; Hu, M. 2014. Committed versus contingent pricing under competition, Production and Operations Management 23(11): 1919–1936. https://doi.org/10.1111/poms.12202
Weber, C. A.; Current, J. R.; Benton, W. C. 1991. Vendor selection criteria and methods, European Journal of Operational Research 50(1): 2–18. https://doi.org/10.1016/0377–2217(91)90033-R
Yahya, S.; Kingsman, B. 1999. Vendor rating for an entrepreneur development programme: a case study using the analytic hierarchy process method, Journal of the Operational Research Society 50(9): 916–930. https://doi.org/10.1057/palgrave.jors.2600797
Yang, J. L.; Chiu, H. N.; Tzeng, G. H.; Yeh, R. H. 2008. Vendor selection by integrated fuzzy MCDM techniques with independent and interdependent relationships, Information Sciences 178(21): 4166–4183. https://doi.org/10.1016/j.ins.2008.06.003
Yin, M.; Kim, K. H. 2012. Quantity discount pricing for container transportation services by shipping lines, Computers and Industrial Engineering 63(1): 313–322. https://doi.org/10.1016/j.cie.2012.03.008
Zeng, J.; An, M.; Smith, N. J. 2007. Application of a fuzzy based decision making methodology to construction project risk assessment, International Journal of Project Management 25(6): 589–600. https://doi.org/10.1016/j.ijproman.2007.02.006