کاربرد شبکه های عصبی مصنوعی برای شناسایی مشتریان راضی خدمات پس از فروش خودرو
محورهای موضوعی : مدیریت بازرگانیعلیرضا فضل زاده 1 , محمدصادق زینلی کرمانی 2
1 - عضو هیئت علمی(استادیار) دانشگاه تبریز
2 - دانشجوی کارشناسی ارشد مدیریت بازرگانی مؤسسه آموزش عالی ارس تبریز
کلید واژه: رضایت مشتری, خدمات پس از فروش خودرو, شبکه های عصبی چند لایه, استراتژی بازاریابی,
چکیده مقاله :
هدف این تحقیق توسعه یک مدل از شبکه های عصبی برای شناسایی مشتریان راضی برای بازاریابی ارایه سرویس های تعمیراتی خودروها بود. داده ها از بررسی ده سرویس دهنده خدمات خودرویی در ایران بدست آمدند. شبکه های عصبی چند لایه با تابع آموزش تانژانت هایپربولیک با الگوریتم آموزشی پیش خور برای ساخت مدل شناسایی به کار گرفته شد. نتایج مشخص ساخت که دقت مدل شناسایی آزمایش روی مدل بزرگتر از آن است که اتفاقی به نظر برسد. در خلال یک سری وزن های خاص موجود، اعتبار کلی هر یک از متغیرهای مستقل تولید شده کاملاً روشن می شود. این تحقیق تایید کرد که مدل شبکه عصبی برای شناخت الگوهای موجود داده های مشتری قابل استفاده است. مزایای استفاده از نقاط قوت مدل نشان داده شده است. مؤلفان معتقدند که مدل مفید است و به عنوان ابزار تحلیلی برای بازاریاب های خدمات تعمیراتی خودروها برای طراحی استراتژی بازار، مناسب است.
The purpose of the research was the development of a neural networks model to identify satisfied customers for car maintenance service marketing. The data were collected from the survey of ten car maintenance service providers in Iran. Multi-layer perceptron (MLP) neural networks with hyperbolic tangent function trained by feed forward training algorithm were utilized to build the identification model. The result reveals that the identification accuracy of the test on the model is greater than that expected by chance. Through a set of available contribution weights, the general importance of each independent variable produced is revealed. This research confirms that the neural network model is useful in recognizing the existing patterns of customer’s data. The advantages of using the model are highlighted. Authors believe that the model is useful and suitable as an analyzing tool for car maintenance service on market strategy planning.
Anderson, E.W., Fornell, C. and Lehmann, D.R. (1994), ``Customer satisfaction, market share, and profitability: findings from Sweden'', Journal of Marketing, Vol. 58, July, pp. 53-66.
Anderson, E.W. and Sullivan, M. (1993), “The antecedents and consequences of customer satisfaction for firms”, Marketing Science, Vol. 12 No. 2, pp. 125-43.
Audrain, A. F. (2002). The attribute-satisfaction link over time: A study on panel data. In Proceedings of the 31st EMAC Conference, 28–31 May 2002, University of Minho and European Marketing Academy (EMAC), Braga, Portugal.
Berry, L.L., Zeithaml, V.A. and Parasuraman, A. (1985), “Quality counts in services, too”, Business Horizons, May-June, pp. 44-52.
Bitner, M.J. (1990), ``Evaluating service encounters: the effects of physical surroundings and employee responses'', Journal of Marketing, Vol. 54, April, pp. 69-82.
Biong, H., & Selnes, F. (1996). The strategic role of the salesperson in established buyer–seller relationships. Journal of Business-to-Business Marketing, 3, pp. 39–78.
Bishop, C. M. (1995). Neural networks for pattern recognition. Oxford: Oxford University Press.
Boulding, W., Kalra, A., Staelin, R. and Zeithaml, V. (1993), “A dynamic process model of service quality: from expectations to behavioural intentions”, Journal of Marketing Research, Vol. 30, February, pp. 7-27.
Bolton, R.N. and Drew, J.H. (1991), “A multi-stage model of customers’ assessments of service quality and value”, Journal of Consumer Research, Vol. 17, pp. 375-84.
Bolton, R.N. (1998), “A dynamic model of the duration of the customer’s relationship with a continuous service provider: the role of customer satisfaction”, Marketing Science, Vol. 17 No. 1, pp. 45-65.
Brown, T.J., Churchill, G.A. Jr and Peter, P.J. (1993), “Improving the measurement of service quality”, Journal of Retailing, Vol. 69, Spring, pp. 127-38.
Callan, R. (1999). The essence of neural networks. London: Prentice Hall Europe.
Carman, J.M. (1990), ``Consumer perceptions of service quality: an assessment of the SERVQUAL dimensions'', Journal of Retailing, Vol. 66, Spring, pp. 35-55.
Cronin, J.J. and Taylor, S.A. (1992), ``Measuring service quality: a re-examination and extension'', Journal of Marketing, Vol. 56, July, pp. 55-68.
Crooks & Ted (1995). Marketing with neural networks or, you gotta know the territory. Credit World, 84(2), 18–20.
Cuieford, J. P. (1965). Fundamental statistics in psychology and education (4th Ed.). New York: McGraw-Hill.
Curry, B., & Moutinho, L. (1993). Neural networks in marketing: Modeling consumer responses to advertising stimuli. European Journal of Marketing, 27(7), pp. 5–20.
Dabholkar, P.A., Thorpe, D.I. and Rentz, J.O. (1996), ``A measure of service quality for retail stores: scale development and validation'', Journal of the Academy of Marketing Science, Vol. 24, Winter, pp. 3-16.
Dasgupta, C., Ghose, D., Gary, S., & Ghose, S. (1994). Comparing the predictive performance of a neural network model with some traditional market response models. International Journal of Forecasting, 10(2), pp. 235–244.
Fausett, L. (1994). Fundamentals of neural networks. Upper Saddle River, NJ: Prentice-Hall.
Fish, K. E., Barnes, H. J., & Aiken, W. M. (1995). Artificial neural networks: a new methodology for industrial market segmentation. Industrial Marketing Management, 24(5), pp. 431–439.
Fisk, R.P., Brown, S.W. and Bitner, M.J. (1993), ``Tracking the evolution of the services marketing literature'', Journal of Retailing, Vol. 69, Spring, pp. 61-103.
GroÈnroos, C. (1985), ``Internal marketing ± theory and practice'', in Block, T.M., Upah, G.D. and Zeithaml,V.A. (Eds), Services Marketing in a Changing Environment, American Marketing Association, Chicago, IL, pp. 41-7.
Grønholdt, L., & Martensen, A. (2005). Analyzing customer satisfaction data: a comparison of regression and artificial neural networks. International Journal of Market Research, 47(2), pp. 121–130.
Hackl, P., & Westlund, W. A. (2000). On structural equation modeling for customer satisfaction measurement. Total Quality Management, 11(4/ 5/6), pp. 820–825.
Hassoum, M. H. (1995). Fundamentals of artificial neural networks. Cambridge: MIT Press.
Haykin, S. (1999). Neural networks: A comprehensive foundation.Prentice Hall, Inc.
Heskett, J.L., Sasser, W.E. Jr and Schlesinger, L.A. (1997), The Service-Profit Chain, Free Press, New York, NY.
Hill, N. (2006). Customer Satisfaction Measurement. Translated by: M. Eskandari. Tehran: Rasa Publication, (In Persian).
Holbrook, M. (1994), ``The nature of customer value: an anthology of services in the consumption experience'', in Rust, R.T. and Oliver, R.L. (Eds), Service Quality: New Directions in Theory and Practice, Sage Publications, Thousand Oaks, CA, pp. 21-71.
Hu, M. Y., Shanker, M., & Hung, S. M. (1999). Estimation of posterior probabilities of consumer situational choices with neural network classifiers. International Journal of Research in Marketing, 16(4), pp. 307–317.
Johnston, R. and Lyth, D. (1991), “Service quality: implementing the integration of customer expectations and operational capability”, in Brown, S.W., Gummesson, E., Edvardsson, B. and Gustavsson, B. (Eds), Service Quality: Multidisciplinary and Multinational Perspectives, Lexington Books, Lexington, MA.
Kaefer, F., Heilman, M. C., & Ramenofsky, D. S. (2005). A neural network application to consumer classification to improve the timing of direct marketing activities. Computers & Operations Research, 32, pp. 2595–2615.
Kim, Y. S., Street, N. W., Russell, J. G., & Menczer, F. (2005). Customer targeting: A neural network approach guided by genetic algorithms. Management Science, 51(2), pp. 264–276.
Lemmink, J., de Ruyter, K. and Wetzels, M. (1998), ``The role of value in the delivery process of hospitality services'', Journal of Economic Psychology, Vol. 19, April, pp. 159-77.
Lensberg, T., Eilifsen, A., & McKee, T. E. (2006). Bankruptcy theory development and classification via genetic programming. European Journal of Operational Research, 169(2), pp. 677–697.
McDougall, G. and Levesque, T. (1992), ``The measurement of service quality: some methodological issues'', 2nd International Research Seminar in Service Management, La-Londe-Les Maures, France, pp. 410-31.
Michalski, R. S. (1983). A theory and methodology of inductive learning. Artificial Intelligence, 20, pp. 111–161.
Morgan, N.A. and Piercy, N.F. (1992), ``Market-led quality'', Industrial Marketing Management, Vol. 21, pp. 111-18.
Nelson, M. M., & Illingworth, W. T. (1994). Practical guide to neural nets. USA: Addison Wesley Publishing Company.
Nunnally, J. (1978). Psychometric theory. New York: McGraw-Hill.
OECD (2004), Passenger Cars, OECD Main Economic Indicators (MEI), Organization for Economic Co Operation and Development, Paris, September, p. 10.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1991a), ``Refinement and reassessment of the SERVQUAL scale'', Journal of Retailing, Vol. 67, Winter, pp. 420-50.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1991b), ``Understanding customer expectations of service'', Sloan Management Review, Vol. 39, spring, pp. 39-48.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985), ``A conceptual model of service quality and its implications for future research'', Journal of Marketing, Vol. 49, fall, pp. 41-50.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), “SERVQUAL: a multiple-item scale for measuring customer perceptions of service quality”, Journal of Retailing, Vol. 64 No. 1, pp. 12-40.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1993),``More on improving service quality measurement'', Journal of Retailing, Vol. 69, Spring, pp. 140-7.
Peterson, R.A. and Wilson, W.R. (1992), ``Measuring customer satisfaction: fact and artifact'', Journal of the Academy of Marketing Science, Vol. 20, pp. 61-71.
Ravald, A. and GroÈnroos, C. (1996), ``the value concept and relationship marketing'', European Journal of Marketing, Vol. 30 No. 2, pp. 19-30.
Reichheld, F.F. (1996), the Loyalty Effect, Harvard Business School Press, Boston, MA.
Rumelhart, D. E., & McClelland, J. L. (1986). Parallel distributed processing. Cambridge, MA: MIT press.
Schocken, S., & Ariav, G. (1994). Neural networks for decision support: Problems and opportunities. Decision Support Systems, 11(5), pp. 393– 414.
Sekaran, U. (2000). Research methods for business. John Wiley and Sons, Inc.
Sharda, R. (1994). Neural networks for the MS/OR analyst: An application bibliography. Interfaces, 24(2), pp. 116–130.
Sollner, A. (1998). Implementing customer orientation. Thexis Fachzeitschrift for Marketing, 14, pp. 44–49.
Spangler, W. E., May, J. H., & Vargas, L. G. (1999). Choosing datamining methods for multiple classification: Representational and performance measurement implications for decision support. Journal of Management Information Systems, 16(1), pp. 37–62.
Taylor, S.A. and Baker, T.L. (1994), ``An assessment of the relationship between service quality and customer satisfaction in the formation of consumers' purchase intentions'', Journal of Marketing, Vol. 58, summer, pp. 163-78.
Teas, R.K. (1993), ``Expectations, performance evaluation and consumers' perceptions of quality'', Journal of Marketing, Vol. 57, October, pp. 18-34.
Venugopal, V., & Baets, W. (1994). Neural networks and their applications in marketing management. Journal of Systems Management, 45(9), pp. 16–21.
Ville, B. de. (1996). Predictive models in market research. Marketing Research, 8(2), pp. 43–45.
Wanger, H. C., Fleming, D., & LaForge, R. W. (1994). Relationship Marketing in Health Care. Journal of Health Care Marketing, 14(4), pp. 42–48.
Webster, F. E. (1992). The changing role of marketing in the corporation. Journal of Marketing, 56, p. 1 17.
Willson, E., & Wragg, T. (2001). We cannot diagnose the patient’s illnessbut experience tells us what treatment works. International Journal of Market Research, 43(2), pp. 189–215.
Wittink, D.R. and Bayer, L.R. (1994), “The measurement imperative”, Marketing Research, Vol. 6, pp. 14-23.
Woodruff, R.B. (1997), ``Customer value: the next source for competitive advantage'', Journal of the Academy of Marketing Science, Vol. 25 No. 2, spring, pp. 139-53.
Yi, Y. (1990), ``A critical review of consumer satisfaction'', in Zeithaml, V.A. (Ed.), Review of Marketing, American Marketing Association, Chicago, IL, pp. 68-123.
Yi, Y. (1991). A critical review of consumer satisfaction. In V. A. Zeithaml (Ed.), Review of marketing 1990 (pp. 68–123). Chicago, IL: American Marketing Association.
Zahavi, J., & Levin, N. (1997). Applying neural computing to target marketing. Journal of Direct Marketing, 11(4), pp. 76–93.
Zarei Matin, H. (2009). Advanced Organizational Behavior Management. Tehran: Agah Publication , (In Persian).
Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1996), “The behavioral consequences of service quality”, Journal of Marketing, Vol. 60 No. 2, pp. 31-46.
Zeithaml, V.A. (1988), ``Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence'', Journal of Marketing, Vol. 52, July, pp. 2-22.
Zhang, G., Hu, M., Patuwo, B. E., & Indro, D. C. (1999). Artificial neural networks in bankruptcy prediction: general framework and cross validation analysis. European Journal of Operational Research, 116(1), pp. 16–32.
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Anderson, E.W., Fornell, C. and Lehmann, D.R. (1994), ``Customer satisfaction, market share, and profitability: findings from Sweden'', Journal of Marketing, Vol. 58, July, pp. 53-66.
Anderson, E.W. and Sullivan, M. (1993), “The antecedents and consequences of customer satisfaction for firms”, Marketing Science, Vol. 12 No. 2, pp. 125-43.
Audrain, A. F. (2002). The attribute-satisfaction link over time: A study on panel data. In Proceedings of the 31st EMAC Conference, 28–31 May 2002, University of Minho and European Marketing Academy (EMAC), Braga, Portugal.
Berry, L.L., Zeithaml, V.A. and Parasuraman, A. (1985), “Quality counts in services, too”, Business Horizons, May-June, pp. 44-52.
Bitner, M.J. (1990), ``Evaluating service encounters: the effects of physical surroundings and employee responses'', Journal of Marketing, Vol. 54, April, pp. 69-82.
Biong, H., & Selnes, F. (1996). The strategic role of the salesperson in established buyer–seller relationships. Journal of Business-to-Business Marketing, 3, pp. 39–78.
Bishop, C. M. (1995). Neural networks for pattern recognition. Oxford: Oxford University Press.
Boulding, W., Kalra, A., Staelin, R. and Zeithaml, V. (1993), “A dynamic process model of service quality: from expectations to behavioural intentions”, Journal of Marketing Research, Vol. 30, February, pp. 7-27.
Bolton, R.N. and Drew, J.H. (1991), “A multi-stage model of customers’ assessments of service quality and value”, Journal of Consumer Research, Vol. 17, pp. 375-84.
Bolton, R.N. (1998), “A dynamic model of the duration of the customer’s relationship with a continuous service provider: the role of customer satisfaction”, Marketing Science, Vol. 17 No. 1, pp. 45-65.
Brown, T.J., Churchill, G.A. Jr and Peter, P.J. (1993), “Improving the measurement of service quality”, Journal of Retailing, Vol. 69, Spring, pp. 127-38.
Callan, R. (1999). The essence of neural networks. London: Prentice Hall Europe.
Carman, J.M. (1990), ``Consumer perceptions of service quality: an assessment of the SERVQUAL dimensions'', Journal of Retailing, Vol. 66, Spring, pp. 35-55.
Cronin, J.J. and Taylor, S.A. (1992), ``Measuring service quality: a re-examination and extension'', Journal of Marketing, Vol. 56, July, pp. 55-68.
Crooks & Ted (1995). Marketing with neural networks or, you gotta know the territory. Credit World, 84(2), 18–20.
Cuieford, J. P. (1965). Fundamental statistics in psychology and education (4th Ed.). New York: McGraw-Hill.
Curry, B., & Moutinho, L. (1993). Neural networks in marketing: Modeling consumer responses to advertising stimuli. European Journal of Marketing, 27(7), pp. 5–20.
Dabholkar, P.A., Thorpe, D.I. and Rentz, J.O. (1996), ``A measure of service quality for retail stores: scale development and validation'', Journal of the Academy of Marketing Science, Vol. 24, Winter, pp. 3-16.
Dasgupta, C., Ghose, D., Gary, S., & Ghose, S. (1994). Comparing the predictive performance of a neural network model with some traditional market response models. International Journal of Forecasting, 10(2), pp. 235–244.
Fausett, L. (1994). Fundamentals of neural networks. Upper Saddle River, NJ: Prentice-Hall.
Fish, K. E., Barnes, H. J., & Aiken, W. M. (1995). Artificial neural networks: a new methodology for industrial market segmentation. Industrial Marketing Management, 24(5), pp. 431–439.
Fisk, R.P., Brown, S.W. and Bitner, M.J. (1993), ``Tracking the evolution of the services marketing literature'', Journal of Retailing, Vol. 69, Spring, pp. 61-103.
GroÈnroos, C. (1985), ``Internal marketing ± theory and practice'', in Block, T.M., Upah, G.D. and Zeithaml,V.A. (Eds), Services Marketing in a Changing Environment, American Marketing Association, Chicago, IL, pp. 41-7.
Grønholdt, L., & Martensen, A. (2005). Analyzing customer satisfaction data: a comparison of regression and artificial neural networks. International Journal of Market Research, 47(2), pp. 121–130.
Hackl, P., & Westlund, W. A. (2000). On structural equation modeling for customer satisfaction measurement. Total Quality Management, 11(4/ 5/6), pp. 820–825.
Hassoum, M. H. (1995). Fundamentals of artificial neural networks. Cambridge: MIT Press.
Haykin, S. (1999). Neural networks: A comprehensive foundation.Prentice Hall, Inc.
Heskett, J.L., Sasser, W.E. Jr and Schlesinger, L.A. (1997), The Service-Profit Chain, Free Press, New York, NY.
Hill, N. (2006). Customer Satisfaction Measurement. Translated by: M. Eskandari. Tehran: Rasa Publication, (In Persian).
Holbrook, M. (1994), ``The nature of customer value: an anthology of services in the consumption experience'', in Rust, R.T. and Oliver, R.L. (Eds), Service Quality: New Directions in Theory and Practice, Sage Publications, Thousand Oaks, CA, pp. 21-71.
Hu, M. Y., Shanker, M., & Hung, S. M. (1999). Estimation of posterior probabilities of consumer situational choices with neural network classifiers. International Journal of Research in Marketing, 16(4), pp. 307–317.
Johnston, R. and Lyth, D. (1991), “Service quality: implementing the integration of customer expectations and operational capability”, in Brown, S.W., Gummesson, E., Edvardsson, B. and Gustavsson, B. (Eds), Service Quality: Multidisciplinary and Multinational Perspectives, Lexington Books, Lexington, MA.
Kaefer, F., Heilman, M. C., & Ramenofsky, D. S. (2005). A neural network application to consumer classification to improve the timing of direct marketing activities. Computers & Operations Research, 32, pp. 2595–2615.
Kim, Y. S., Street, N. W., Russell, J. G., & Menczer, F. (2005). Customer targeting: A neural network approach guided by genetic algorithms. Management Science, 51(2), pp. 264–276.
Lemmink, J., de Ruyter, K. and Wetzels, M. (1998), ``The role of value in the delivery process of hospitality services'', Journal of Economic Psychology, Vol. 19, April, pp. 159-77.
Lensberg, T., Eilifsen, A., & McKee, T. E. (2006). Bankruptcy theory development and classification via genetic programming. European Journal of Operational Research, 169(2), pp. 677–697.
McDougall, G. and Levesque, T. (1992), ``The measurement of service quality: some methodological issues'', 2nd International Research Seminar in Service Management, La-Londe-Les Maures, France, pp. 410-31.
Michalski, R. S. (1983). A theory and methodology of inductive learning. Artificial Intelligence, 20, pp. 111–161.
Morgan, N.A. and Piercy, N.F. (1992), ``Market-led quality'', Industrial Marketing Management, Vol. 21, pp. 111-18.
Nelson, M. M., & Illingworth, W. T. (1994). Practical guide to neural nets. USA: Addison Wesley Publishing Company.
Nunnally, J. (1978). Psychometric theory. New York: McGraw-Hill.
OECD (2004), Passenger Cars, OECD Main Economic Indicators (MEI), Organization for Economic Co Operation and Development, Paris, September, p. 10.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1991a), ``Refinement and reassessment of the SERVQUAL scale'', Journal of Retailing, Vol. 67, Winter, pp. 420-50.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1991b), ``Understanding customer expectations of service'', Sloan Management Review, Vol. 39, spring, pp. 39-48.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985), ``A conceptual model of service quality and its implications for future research'', Journal of Marketing, Vol. 49, fall, pp. 41-50.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), “SERVQUAL: a multiple-item scale for measuring customer perceptions of service quality”, Journal of Retailing, Vol. 64 No. 1, pp. 12-40.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1993),``More on improving service quality measurement'', Journal of Retailing, Vol. 69, Spring, pp. 140-7.
Peterson, R.A. and Wilson, W.R. (1992), ``Measuring customer satisfaction: fact and artifact'', Journal of the Academy of Marketing Science, Vol. 20, pp. 61-71.
Ravald, A. and GroÈnroos, C. (1996), ``the value concept and relationship marketing'', European Journal of Marketing, Vol. 30 No. 2, pp. 19-30.
Reichheld, F.F. (1996), the Loyalty Effect, Harvard Business School Press, Boston, MA.
Rumelhart, D. E., & McClelland, J. L. (1986). Parallel distributed processing. Cambridge, MA: MIT press.
Schocken, S., & Ariav, G. (1994). Neural networks for decision support: Problems and opportunities. Decision Support Systems, 11(5), pp. 393– 414.
Sekaran, U. (2000). Research methods for business. John Wiley and Sons, Inc.
Sharda, R. (1994). Neural networks for the MS/OR analyst: An application bibliography. Interfaces, 24(2), pp. 116–130.
Sollner, A. (1998). Implementing customer orientation. Thexis Fachzeitschrift for Marketing, 14, pp. 44–49.
Spangler, W. E., May, J. H., & Vargas, L. G. (1999). Choosing datamining methods for multiple classification: Representational and performance measurement implications for decision support. Journal of Management Information Systems, 16(1), pp. 37–62.
Taylor, S.A. and Baker, T.L. (1994), ``An assessment of the relationship between service quality and customer satisfaction in the formation of consumers' purchase intentions'', Journal of Marketing, Vol. 58, summer, pp. 163-78.
Teas, R.K. (1993), ``Expectations, performance evaluation and consumers' perceptions of quality'', Journal of Marketing, Vol. 57, October, pp. 18-34.
Venugopal, V., & Baets, W. (1994). Neural networks and their applications in marketing management. Journal of Systems Management, 45(9), pp. 16–21.
Ville, B. de. (1996). Predictive models in market research. Marketing Research, 8(2), pp. 43–45.
Wanger, H. C., Fleming, D., & LaForge, R. W. (1994). Relationship Marketing in Health Care. Journal of Health Care Marketing, 14(4), pp. 42–48.
Webster, F. E. (1992). The changing role of marketing in the corporation. Journal of Marketing, 56, p. 1 17.
Willson, E., & Wragg, T. (2001). We cannot diagnose the patient’s illnessbut experience tells us what treatment works. International Journal of Market Research, 43(2), pp. 189–215.
Wittink, D.R. and Bayer, L.R. (1994), “The measurement imperative”, Marketing Research, Vol. 6, pp. 14-23.
Woodruff, R.B. (1997), ``Customer value: the next source for competitive advantage'', Journal of the Academy of Marketing Science, Vol. 25 No. 2, spring, pp. 139-53.
Yi, Y. (1990), ``A critical review of consumer satisfaction'', in Zeithaml, V.A. (Ed.), Review of Marketing, American Marketing Association, Chicago, IL, pp. 68-123.
Yi, Y. (1991). A critical review of consumer satisfaction. In V. A. Zeithaml (Ed.), Review of marketing 1990 (pp. 68–123). Chicago, IL: American Marketing Association.
Zahavi, J., & Levin, N. (1997). Applying neural computing to target marketing. Journal of Direct Marketing, 11(4), pp. 76–93.
Zarei Matin, H. (2009). Advanced Organizational Behavior Management. Tehran: Agah Publication , (In Persian).
Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1996), “The behavioral consequences of service quality”, Journal of Marketing, Vol. 60 No. 2, pp. 31-46.
Zeithaml, V.A. (1988), ``Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence'', Journal of Marketing, Vol. 52, July, pp. 2-22.
Zhang, G., Hu, M., Patuwo, B. E., & Indro, D. C. (1999). Artificial neural networks in bankruptcy prediction: general framework and cross validation analysis. European Journal of Operational Research, 116(1), pp. 16–32.
