Developing a new data envelopment analysis model for customer value analysis

Mahdi Mahdiloo; Abdollah Noorizadeh; Reza Farzipoor Saen

doi:10.3934/jimo.2011.7.531

Article Contents

2011, Volume 7, Issue 3: 531-558. Doi: 10.3934/jimo.2011.7.531

This issue Previous Article On symmetric and self duality in vector optimization problem Next Article Weak nonlinear bilevel problems: Existence of solutions via reverse convex and convex maximization problems

Developing a new data envelopment analysis model for customer value analysis

1.
Department of Industrial Management, Faculty of Management and Accounting, Islamic Azad University-Karaj Branch, P. O. Box: 31485-313, Karaj

Received: February 28, 2010

Revised: February 28, 2011

Published: June 2011

Abstract Related Papers Cited by

Abstract

This paper proposes an application of data envelopment analysis (DEA) to measure the value of customers. In order to distinguish between expectations and needs of profitable and unprofitable customers and to allocate marketing investments among them, customers are compared with each other and ranked in a customer value pyramid. To this end, we use a combination of the Banker, Charnes and Cooper (BCC) model [3], assurance region (AR) model, and cross-efficiency evaluation. A numerical example demonstrates the application of the proposed model in an Iranian manufacturing company.

Keywords:

Mathematics Subject Classification: Primary: 90C05; Secondary: 90B60.

Citation:

Related Papers

Cited by

References

[1]	D. A. Aaker, V. Kumar and G. S. Day, "Marketing Research," John Wiley & Sons, New York, 2001.
[2]	J. Anderson and J. Narus, "Business Market Management: Understanding, Creating and Developing Value," 2nd edition, Prentice-Hall, Englewood Cliffs, NJ, 2004.
[3]	R. D. Banker, A. Charnes and W. W. Cooper, Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science, 30 (1984), 1078-1092.doi: 10.1287/mnsc.30.9.1078.
[4]	D. Bowman and D. Narayandas, Managing customer-initiated contacts with manufacturers: The impact on share of category requirements and word-of mouth behavior, Journal of Marketing Research, 38 (2001), 281-297.doi: 10.1509/jmkr.38.3.281.18863.
[5]	A. Charnes, W. W. Cooper and E. Rhodes, Measuring the efficiency of decision making units, European Journal of Operational Research, 2 (1978), 429-444.doi: 10.1016/0377-2217(78)90138-8.
[6]	M. T. Chu, J. Z. Shyu and R. Khosla, Measuring the relative performance for leading fables firms by using data envelopment analysis, Journal of Intelligent Manufacturing, 19 (2008), 257-272.doi: 10.1007/s10845-008-0079-3.
[7]	R. Colombo and W. Jiang, A stochastic RFM model, Journal of Interactive Marketing, 13 (1999), 2-12.doi: 10.1002/(SICI)1520-6653(199922)13:3<2::AID-DIR1>3.0.CO;2-H.
[8]	W. W. Cooper, L. M. Seiford and K. Tone, "Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software," 2nd edition, Springer, New York, 2007.
[9]	J. Deichmann, A. Eshghi, D. Haughton, S. Sayek and N. Teebagy, Application of Multiple Adaptive Regression Splines (MARS) in direct response modeling, Journal of Interactive Marketing, 16 (2002), 15-27.doi: 10.1002/dir.10040.
[10]	J. Doyle and R. Green, Efficiency and cross efficiency in DEA: Derivations, meanings and the uses, Journal of the Operational Research Society, 45 (1994), 567-578.
[11]	P. Fader, B. Hardie and K. L. Lee, RFM and CLV: Using Iso-value curves for customer base analysis, Journal of Marketing Research, 42 (2005), 415-430.doi: 10.1509/jmkr.2005.42.4.415.
[12]	R. Garland, Segmenting retail banking customers, Journal of Financial Services Marketing, 10 (2005), 179-191.doi: 10.1057/palgrave.fsm.4770184.
[13]	F. Grönöl and M. Shi, Optimal mailing of catalogs: A new methodology using estimable structural dynamic programming models, Management Science, 44 (1998), 1249-1262.doi: 10.1287/mnsc.44.9.1249.
[14]	C. Grönroos, From marketing mix to relationship marketing: Towards a paradigm shift in marketing, Management Decision, 32 (1994), 4-20.doi: 10.1108/00251749410054774.
[15]	K. Ha, S. Cho and D. Maclachlan, Response models based on bagging neural networks, Journal of Interactive Marketing, 19 (2005), 17-30.doi: 10.1002/dir.20028.
[16]	L. K. Hansen and P. R. Salamon, Neural network ensembles, IEEE Transactions on Pattern Analysis and Machine Intelligence, 12 (1990), 993-1001.doi: 10.1109/34.58871.
[17]	Z. Huanga, H. Chena, C. J. Hsua, W. H. Chenb and S. Wu, Credit rating analysis with support vector machines and neural networks: A market comparative study, Decision Support Systems, 37 (2004), 543-558.doi: 10.1016/S0167-9236(03)00086-1.
[18]	Y. Kim, W. N. Street, G. J. Russell and F. Menczer, Customer targeting: A neural network approach guided by genetic algorithms, Management Science, 51 (2005), 264-276.doi: 10.1287/mnsc.1040.0296.
[19]	P. J. Korhonen and M. Luptacik, Eco-efficiency analysis of power plants: An extension of data envelopment analysis, European Journal of Operational Research, 154 (2004), 437-446.doi: 10.1016/S0377-2217(03)00180-2.
[20]	J. Liu, F. Y. Ding and V. Lall, Using data envelopment analysis to compare suppliers for supplier selection and performance improvement, Supply Chain Management: An International Journal, 5 (2000), 143-150.
[21]	L. Moutinho, B. Curry, F. Davies and P. Rita, "Neural Network in Marketing," Routledge, New York, 1994.
[22]	P. E. Pfeifer, The optimal ratio of acquisition and retention costs, Journal of Targeting, Measurement and Analysis for Marketing, 13 (2005), 179-188.doi: 10.1057/palgrave.jt.5740142.
[23]	D. Pitta, F. Franzak and D. Fowler, A strategic approach to building online customer loyalty: Integrating customer profitability tiers, Journal of Consumer Marketing, 23 (2006), 421-429.doi: 10.1108/07363760610712966.
[24]	C. K. Prahalad, "The Fortune at the Bottom of the Pyramid: Eradicating Poverty through Profits," Wharton School Publishing, Upper Saddle River, NJ, 2004.
[25]	W. Reinartz and V. Kumar, The mismanagement of customer loyalty, Harvard Business Review, (2002), 86-94.
[26]	T. L. Saaty, "Multicriteria Decision Making: The Analytic Hierarchy Process," 1988, revised and published by the author, original version published by McGraw-Hill, New York, 1980.
[27]	L. M. Seiford and J. Zhu, Identifying excesses and deficits in Chinese industrial productivity (1953-1990): A weighted data envelopment analysis approach, Omega, 26 (1998), 279-296.doi: 10.1016/S0305-0483(98)00011-5.
[28]	L. M. Seiford and J. Zhu, Modeling undesirable factors in efficiency evaluation, European Journal of Operational Research, 142 (2002), 16-20.doi: 10.1016/S0377-2217(01)00293-4.
[29]	T. R. Sexton, R. H. Silkman and A. J. Hogan, Data envelopment analysis: Critique and extensions, in "Measuring Efficiency: An Assessment of Data Envelopment Analysis" (ed. R. H. Silkman), Jossey-Bass, San Francisco, (1986), 73-105.
[30]	R. Shabahang, "Financial Accounting," Iranian Auditing Organization, 8th edition, (in Persian), 2003.
[31]	T. Sueyoshi, J. Shang and W. C. Chiang, A decision support framework for internal audit prioritization in a rental car company: A combined use between DEA and AHP, European Journal of Operational Research, 199 (2009), 219-231.doi: 10.1016/j.ejor.2008.11.010.
[32]	R. G. Thompson, F. D. Singleton, J. R. M. Thrall and B. A. Smith, Comparative site evaluations for locating a high-energy physics lab in Texas, Interfaces, 16 (1986), 35-49.doi: 10.1287/inte.16.6.35.
[33]	E. M. Van Raaij, The strategic value of customer profitability analysis, Marketing Intelligence & Planning, 23 (2005), 372-381.doi: 10.1108/02634500510603474.
[34]	Y.-M. Wang, Y. Luo and L. Liang, Ranking decision making units by imposing a minimum weight restriction in the data envelopment analysis, Journal of Computational and Applied Mathematics, 223 (2009), 469-484.doi: 10.1016/j.cam.2008.01.022.
[35]	W. P. Wong and K. Y. Wong, A review on benchmarking of supply chain performance measures, Benchmarking: An International Journal, 15 (2008), 25-51.
[36]	Y. P. Yu, and S. Q. Cai, A new approach to customer targeting under condition of information shortage, Marketing Intelligence & Planning, 25 (2007), 343-359.doi: 10.1108/02634500710754583.
[37]	V. A. Zeithaml, R. T. Rust and K. N. Lemon, The customer pyramid: Creating and serving profitable customers, California Management Review, 43 (2001), 118-142.
[38]	J. Zhu and W. D. Cook, "Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis," A Problem-Solving Handbook, Springer, New York, US, 2007.