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TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI

Year 2006, Volume: 6 Issue: 2, 105 - 114, 01.10.2006

Ali Özdemir Aslı Özdemir

Abstract

İşletmeler, artan rekabet koşulları altında ayakta kalabilmek ve rekabet edebilmek için karşılaştıkları çeşitli sorunlara ilişkin etkin kararları belirlemek zorund,adırlar. Geleceğe ilişkin verilecek kararlar işletmeler için belirsizlik içerdiğinden, bu kararların alınmasında çeşitli tahminlerin geliştirilmesi gerekmektedir. Bunlardan biri de talep tahminleridir. İşletmelerin ürünlerine olan talebi tahminlemeleri, belirlenecek pazarlama stratejilerinde önemli bir girdi niteliği taşımaktadır. Çalışmanın giriş bölümünde talep yönetimindeki temel kavramlar, kalitatif ve kantitatif talep tahminleme yöntemleri ele alınmakta; literatür taramasında talep tahminlemesine yönelik başlıca çalışmalara yer verilmekte ve son bölümde ürün talebinin tahminlenmesinde kullanılan kantitatif teknikler uygulanmaktadır. Firma verilerine göre seramik ürün grubunun 2006 yılı talep tahminlerinin oluşturulmasında kullanılması gereken en etkin tahminleme yöntemi belirlenmesine yönelik hipotezler geliştirilmiş ve analizler yapılmıştır

References

  • ALON, Ilan., QI, Min., SADOWSKI, Robert J. (2001). Forecasting Aggregate Retail Sales: A Comparison of Artificial Neural Networks and Traditional Methods, Journal of Retailing and Consumer Services, 8(3).
  • BAKER, J.R., FITZPATRICK, K.E. (1986). Determination of an Optimal Forecast Model for Ambulance Demand Using Goal Programming, Journal of Operational Research Society, 37(11).
  • BHATTACHARYA, M.N. (1974). Forecasting the Demand for Telephones in Australia, Applied Statistics, 23(1).
  • BHATTACHARYA, Sutanuka. (1997). “A Comparative Study of Different Methods of Predicting Time Series”, Yayınlanmamış Yüksek Lisans Tezi, Concordia University, Canada.
  • BURGER, C.J.S.C., DOHNAL, M., KATHRADA, M., LAW, R. (2001). A Practitioners Guide to Time-Series Methods for Tourism Demand Forecasting – A Case Study of Durban, South Africa, Tourism Management, 22(4).
  • BUSINGER, Mark P., READ, Robert R. (1999). Identification of Demand Patterns for Selective Processing: A Case Study, Omega, International Journal of Management Science, 27(2).
  • CARLSON, Rodney L., UMBLE, M. Michael. (1980). Statistical Demand Functions for Automobiles and Their Use for Forecasting in an Energy Crisis, The Journal of Business, 53(2).
  • CHU, Ching-Wu., ZHANG, Guoqiang Peter. (2003). A Comparative Study of Linear and Nonlinear Models for Aggregate Retail Sales Forecasting, International Journal of Production Economics, 86(3).
  • DEMİR, Hulusi., GÜMÜŞOĞLU, Şevkinaz. (2003). Üretim Yönetimi-İşlemler Yönetimi. Beta
  • Basım Yayım, 6. Baskı: İstanbul. FILDES, Robert., HASTINGS, Robert. (1994). The Organization and Improvement of Market
  • Forecasting, Journal of the Operational Research Society, 45(1). FREES, Edward W. (1996). Data Analysis Using
  • Regression Models: The Business Perspective. Prentice-Hall: New Jersey. GAVCAR, Erdoğan., ŞEN, Selim., AYTEKIN, Alper. (1999). Türkiye’de Kullanılan Kagıt-Karton
  • Türlerinin Talep Tahminlerinin Belirlenmesi, Tr. Journal of Agriculture and Forestry, TÜBİTAK, 23. GROEBNER, David F., SHANNON, Patrick W., FRY, Phillip C., SMITH, Kent D. (2001). Business
  • Statistics: A Decision-Making Approach. Prentice- Hall, Fifth Ed.: New Jersey. http://www.die.gov.tr (Erişim Tarihi: 12.01.2005)
  • HUSS, William R. (1985). Comparative Analysis of Company Forecasts and Advanced Time Series
  • Techniques Using Annual Electric Utility Energy Sales Data, International Journal of Forecasting, (3). KAMENETZKY, Ricardo D., Shuman, Larry J., Wolfe, Harvey. (1982). Estimating Need and Demand for Prehospital Care, Operations Research, 30(6).
  • KIRBY, Robert M. (1966). A Comparison of Short and Medium Range Statistical Forecasting
  • Methods, Management Science, 13(4), Series B, Managerial. KLASSEN, Robert D., FLORES, Benito E. (2001).
  • Forecasting Practices of Canadian Firms: Survey Results and Comparisons, International Journal of Production Economics, 70(2). KRESS, George J., SNYDER, John. (1994).
  • Forecasting and Market Analysis Techniques: A Practical Approach. Quorum Books: USA. LAW, Rob., AU, Norman. (1999). A Neural
  • Network Model to Forecast Japanese Demand for Travel to Hong Kong, Tourism Management,20(1). MALIK, Mazhar Ali Khan., AHMAD, Iqbal. (1981). Forecasting Demand for Food in Libya
  • Using Confidence Limits, Long Range Planning, (59. MARCHANT, L.J., HOCKLEY, D.J. (1971). A
  • Comparison of Two Forecasting Techniques, The Statistician, 20(3), Forecasting in Practice. MONKS, Joseph G. (1987). Operations
  • Management. McGraw-Hill International Editions, Third Ed.: Singapore. RENDER, Barry., STAIR, Ralph M. (2000).
  • Quantitative Analysis for Management. Prentice- Hall Inc., Seventh Ed: USA. SANDERS, Nada R., MANRODT, Karl B. (2003).
  • The Efficacy of Using Judgmental versus Quantitative Forecasting Methods in Practice, International Journal of Management Science, (6). SANI, B., KINGSMAN, B.G. (1997). Selecting the Best Periodic Inventory Control and Demand
  • Forecasting Methods for Low Demand Items, The Journal of Operational Research Society, 48(7). SCHROEDER, Roger G. (1989). Operations
  • Management: Decision Making in the Operations Function. McGraw-Hill Book Co., Third Ed.: Singapore. SCHULTZ, Carl R. (1987). Forecasting and Inventory Control for Sporadic Demand under
  • Periodic Review, The Journal of the Operational Research Society, 38(5). STEVENSON, William J. (1989). Introduction to
  • Management Science. Irwin Inc.:USA. TEK, Baybars. (1999). Pazarlama İlkeleri: Global
  • Yönetimsel Yaklaşım Türkiye Uygulamaları. Beta Basım Yayım, 8. Baskı: İstanbul. TÜTEK, Hülya., GÜMÜŞOĞLU, Şevkinaz. (2000). İşletme İstatistiği. Barış Yayınları: İzmir.
  • WILLEMAIN, Thomas R., SMART, Charles N., SCHWARZ, Henry F. (2004). A New Approach to
  • Forecasting Intermittent Demand for Service Parts Inventories, International Journal of Forecasting, (3). WINER, Russell S. (1979). An Analysis of the Time-Varying Effects of Advertising: The Case of
  • Lydia Pinkham, Journal of Business, 52(4). ZHOU, S.L., MCMAHON, T.A., WALTON, A., LEWIS, J. (2002). Forecasting Operational Demand for an Urban Water Supply Zone, Journal of Hydrology, 259(1-4).
  • ZOTTERI, Giulio., KALCHSCHMIDT, Matteo., CANIATO, Federico. (2005). The Impact of Aggregation Level on Forecasting Performance, International Journal of Production Economics, 93

Year 2006, Volume: 6 Issue: 2, 105 - 114, 01.10.2006

Ali Özdemir Aslı Özdemir

Abstract

For businesses to survive and compete under increasing competition conditions they must determine the effective decisions about various issues they are faced with. Since the future decisions contain uncertainty for businesses, it is needed to develop various forecasts to make those decisions. One of them is the demand forecasts. Businesses’ forecasting their products’ demand possesses an important input attribute for themarketing strategies to be determined. In the
introduction section of the study, basic concepts in
demand management, qualitative and quantitative
forecasting techniques are being considered; in the
literature review, primary demand forecastingoriented
studies are being mentioned and in the last
section qualitative techniques are being applied to
forecast product demand. According to the business
data, the hypothesis are constructed and analysis
are performed to determine the most effective
forecasting method to produce ceramic product
category’s demand forecasts for 2006.

References

  • ALON, Ilan., QI, Min., SADOWSKI, Robert J. (2001). Forecasting Aggregate Retail Sales: A Comparison of Artificial Neural Networks and Traditional Methods, Journal of Retailing and Consumer Services, 8(3).
  • BAKER, J.R., FITZPATRICK, K.E. (1986). Determination of an Optimal Forecast Model for Ambulance Demand Using Goal Programming, Journal of Operational Research Society, 37(11).
  • BHATTACHARYA, M.N. (1974). Forecasting the Demand for Telephones in Australia, Applied Statistics, 23(1).
  • BHATTACHARYA, Sutanuka. (1997). “A Comparative Study of Different Methods of Predicting Time Series”, Yayınlanmamış Yüksek Lisans Tezi, Concordia University, Canada.
  • BURGER, C.J.S.C., DOHNAL, M., KATHRADA, M., LAW, R. (2001). A Practitioners Guide to Time-Series Methods for Tourism Demand Forecasting – A Case Study of Durban, South Africa, Tourism Management, 22(4).
  • BUSINGER, Mark P., READ, Robert R. (1999). Identification of Demand Patterns for Selective Processing: A Case Study, Omega, International Journal of Management Science, 27(2).
  • CARLSON, Rodney L., UMBLE, M. Michael. (1980). Statistical Demand Functions for Automobiles and Their Use for Forecasting in an Energy Crisis, The Journal of Business, 53(2).
  • CHU, Ching-Wu., ZHANG, Guoqiang Peter. (2003). A Comparative Study of Linear and Nonlinear Models for Aggregate Retail Sales Forecasting, International Journal of Production Economics, 86(3).
  • DEMİR, Hulusi., GÜMÜŞOĞLU, Şevkinaz. (2003). Üretim Yönetimi-İşlemler Yönetimi. Beta
  • Basım Yayım, 6. Baskı: İstanbul. FILDES, Robert., HASTINGS, Robert. (1994). The Organization and Improvement of Market
  • Forecasting, Journal of the Operational Research Society, 45(1). FREES, Edward W. (1996). Data Analysis Using
  • Regression Models: The Business Perspective. Prentice-Hall: New Jersey. GAVCAR, Erdoğan., ŞEN, Selim., AYTEKIN, Alper. (1999). Türkiye’de Kullanılan Kagıt-Karton
  • Türlerinin Talep Tahminlerinin Belirlenmesi, Tr. Journal of Agriculture and Forestry, TÜBİTAK, 23. GROEBNER, David F., SHANNON, Patrick W., FRY, Phillip C., SMITH, Kent D. (2001). Business
  • Statistics: A Decision-Making Approach. Prentice- Hall, Fifth Ed.: New Jersey. http://www.die.gov.tr (Erişim Tarihi: 12.01.2005)
  • HUSS, William R. (1985). Comparative Analysis of Company Forecasts and Advanced Time Series
  • Techniques Using Annual Electric Utility Energy Sales Data, International Journal of Forecasting, (3). KAMENETZKY, Ricardo D., Shuman, Larry J., Wolfe, Harvey. (1982). Estimating Need and Demand for Prehospital Care, Operations Research, 30(6).
  • KIRBY, Robert M. (1966). A Comparison of Short and Medium Range Statistical Forecasting
  • Methods, Management Science, 13(4), Series B, Managerial. KLASSEN, Robert D., FLORES, Benito E. (2001).
  • Forecasting Practices of Canadian Firms: Survey Results and Comparisons, International Journal of Production Economics, 70(2). KRESS, George J., SNYDER, John. (1994).
  • Forecasting and Market Analysis Techniques: A Practical Approach. Quorum Books: USA. LAW, Rob., AU, Norman. (1999). A Neural
  • Network Model to Forecast Japanese Demand for Travel to Hong Kong, Tourism Management,20(1). MALIK, Mazhar Ali Khan., AHMAD, Iqbal. (1981). Forecasting Demand for Food in Libya
  • Using Confidence Limits, Long Range Planning, (59. MARCHANT, L.J., HOCKLEY, D.J. (1971). A
  • Comparison of Two Forecasting Techniques, The Statistician, 20(3), Forecasting in Practice. MONKS, Joseph G. (1987). Operations
  • Management. McGraw-Hill International Editions, Third Ed.: Singapore. RENDER, Barry., STAIR, Ralph M. (2000).
  • Quantitative Analysis for Management. Prentice- Hall Inc., Seventh Ed: USA. SANDERS, Nada R., MANRODT, Karl B. (2003).
  • The Efficacy of Using Judgmental versus Quantitative Forecasting Methods in Practice, International Journal of Management Science, (6). SANI, B., KINGSMAN, B.G. (1997). Selecting the Best Periodic Inventory Control and Demand
  • Forecasting Methods for Low Demand Items, The Journal of Operational Research Society, 48(7). SCHROEDER, Roger G. (1989). Operations
  • Management: Decision Making in the Operations Function. McGraw-Hill Book Co., Third Ed.: Singapore. SCHULTZ, Carl R. (1987). Forecasting and Inventory Control for Sporadic Demand under
  • Periodic Review, The Journal of the Operational Research Society, 38(5). STEVENSON, William J. (1989). Introduction to
  • Management Science. Irwin Inc.:USA. TEK, Baybars. (1999). Pazarlama İlkeleri: Global
  • Yönetimsel Yaklaşım Türkiye Uygulamaları. Beta Basım Yayım, 8. Baskı: İstanbul. TÜTEK, Hülya., GÜMÜŞOĞLU, Şevkinaz. (2000). İşletme İstatistiği. Barış Yayınları: İzmir.
  • WILLEMAIN, Thomas R., SMART, Charles N., SCHWARZ, Henry F. (2004). A New Approach to
  • Forecasting Intermittent Demand for Service Parts Inventories, International Journal of Forecasting, (3). WINER, Russell S. (1979). An Analysis of the Time-Varying Effects of Advertising: The Case of
  • Lydia Pinkham, Journal of Business, 52(4). ZHOU, S.L., MCMAHON, T.A., WALTON, A., LEWIS, J. (2002). Forecasting Operational Demand for an Urban Water Supply Zone, Journal of Hydrology, 259(1-4).
  • ZOTTERI, Giulio., KALCHSCHMIDT, Matteo., CANIATO, Federico. (2005). The Impact of Aggregation Level on Forecasting Performance, International Journal of Production Economics, 93
There are 35 citations in total.

Details

Other ID JA89FH72DJ
Journal Section Research Article
Authors

Ali Özdemir This is me

Aslı Özdemir This is me

Publication Date October 1, 2006
Published in Issue Year 2006 Volume: 6 Issue: 2

Cite

APA Özdemir, A., & Özdemir, A. (2006). TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI. Ege Academic Review, 6(2), 105-114.
AMA Özdemir A, Özdemir A. TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI. ear. October 2006;6(2):105-114.
Chicago Özdemir, Ali, and Aslı Özdemir. “TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI”. Ege Academic Review 6, no. 2 (October 2006): 105-14.
EndNote Özdemir A, Özdemir A (October 1, 2006) TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI. Ege Academic Review 6 2 105–114.
IEEE A. Özdemir and A. Özdemir, “TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI”, ear, vol. 6, no. 2, pp. 105–114, 2006.
ISNAD Özdemir, Ali - Özdemir, Aslı. “TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI”. Ege Academic Review 6/2 (October 2006), 105-114.
JAMA Özdemir A, Özdemir A. TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI. ear. 2006;6:105–114.
MLA Özdemir, Ali and Aslı Özdemir. “TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI”. Ege Academic Review, vol. 6, no. 2, 2006, pp. 105-14.
Vancouver Özdemir A, Özdemir A. TALEP TAHMİNLEMESİNDE KULLANILAN YÖNTEMLERİN KARŞILAŞTIRILMASI: SERAMİK ÜRÜN GRUBU FİRMA UYGULAMASI. ear. 2006;6(2):105-14.