Research Article
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Determination of Consumer Preferences for Goose Meat Using Conjoint Analysis

Year 2020, Volume: 1 Issue: 2, 62 - 75, 31.12.2020

Selim Gündüz

Abstract

This study examines the consumer preferences for goose meat purchases of consumers who had previously purchased goose meat. The main purpose of this study is to determine which factors are more important for consumers when purchasing goose meat. Accordingly, the conjoint analysis technique, which is one of the multivariate statistical analysis methods, is used to determine the factors affecting goose meat purchases and the reasons for preferring goose meat. According to data of the Turkish Statistical Institute (TURKSTAT) for 2019, 44.07% of the goose population of Turkey (1,157,049) spread among the provinces of Kars (27.26%), Ardahan (8.68%), and Mus (8.13%). A sample of 172 people was selected by using the convenience sampling technique, one of the non-probability sampling methods, among the people who lived or have been living in these provinces and consumed goose meat. Market research and a questionnaire, which was prepared to determine consumer preferences, were conducted on this sample. According to the results of the analysis, the most significant factor determining the consumer preference for goose meat was found to be the price of goose meat per kilo (37.3%). This was followed by the region where the goose was raised (32.8%), the place where the goose meat was sold (21.6%), and the presence of the product label (8.3%) with the identification information of the product. Considering the results of the data obtained from the study, it is thought that the market share of the goose meat will increase if its recognition is increased by applying a reasonable pricing strategy, and standardizing the quality of the product.

Keywords

Goose Meat Consumer Preferences Market Research Conjoint Analysis

Supporting Institution

the Scientific Research Projects (BAP) Coordination Unit of Adana Alparslan Türkeş University of Science and Technology.

Project Number

BAP project No. 18113008

Thanks

This research was supported by the Scientific Research Projects Coordination Unit of Adana Alparslan Turkes University of Science and Technology within the scope of the scientific research projects (Project No: 18113008).

References

  • [1] Aktaş, S., Akkuş, Ö. and Osmanoğlu, S. (2012). A Practical Study on the Performances of the Conditional Logit and Conjoint Analyses in the Modelling of the Polychotomous Dependent Variable. Istanbul Commerce University Journal of Science, 11(21): 25-40.
  • [2] Álvarez-Farizo, B. and Hanley, N. (2002). Using Conjoint Analysis to Quantify Public Preferences over the Environmental Impacts of Wind Farms. An Example from Spain. Energy Policy, 30(2): 107-116.
  • [3] Arslan, C. (2018). Kazların Ekstansif, Yarı Entansif ve Entensif Üretim Sistemlerine Göre Belirlenmesi. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 85-94.
  • [4] Aşkın, Y. and İlaslan, M. (1976). Kars Bölgesi Kazlarında Ekonomik Önemi Olan Bazı Karakterler Üzerinde Araştırmalar. Ankara Üniversitesi Ziraat Fakültesi Yıllığı, 26: 542-552.
  • [5] Baki, F., Saner, G., Adanacıoğlu, H., and Güler, D. (2017). A Conjoint Analysis of Consumer Preferences for Honeydew Honey in Turkey: A Case of İzmir Province. Balkan and Near Eastern Journal of Social Sciences, 3(2): 50-57.
  • [6] Boz, M.A. and Sarıca, M. (2018). Türkiye’de Kaz Yetiştiriciliğinin Durumu ve Geleceği. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 36-44.
  • [7] Bridges, J. F., Hauber, A. B., Marshall, D., Lloyd, A., Prosser, L. A., Regier, D. A., Johnson, F. R., and Mauskopf, J. (2011). Conjoint Analysis Applications in Health a Checklist: A Report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. Value in Health, 14(4): 403-413.
  • [8] Çamlıdere, Ö. (2005). Conjoint Analysis and an Application to Mobile Phones Preference. Master Thesis, Gazi University, Institute of Natural and Applied Sciences, Ankara, 64 pp.
  • [9] Çatpınar, H. (2005). Özel Sağlık Sigortalarında Konjoint Analizi ile Tüketici Tercihi. Sigorta Araştırmaları Dergisi, 1.
  • [10] Çetinel, B. and Yeniay, O. (1997). Konjoint Analiz ve Cep Telefonu Pazarı Üzerine Bir Araştırma. 3. Ulusal Ekonometri ve İstatistik Sempozyumu Bildiri Kitabı, Bursa, 15-24.
  • [11] Çevik, O. and Yiğit, A. M. (2011). Determining Office Furniture Consumers’ Preferences with Conjoint Analysis. Karamanoglu Mehmetbey University Journal of Social and Economic Research, 13 (20): 105-110.
  • [12] Ceylan, H. H. (2013). Market Segmentation Based on Benefit in Retail Sector by Using Conjoint and Cluster Analysis. CBU, Journal of Management and Economics, 20(1): 141-154.
  • [13] Deniz Akıncı, E., Bacanlı, S., and Kıroğlu, G. (2007). Adaptive Conjoint Analysis and an Application on Istanbul Discount Markets. Journal of Dogus University, 8 (1): 1-11.
  • [14] Dikici, T. (2006). Conjoint Analysis and an Application in Connection with Determination of Mobile Phone Preference of Consumers. Master Thesis, Uludag University, Institute of Social Sciences, Econometrics Department, Bursa, 113 pp.
  • [15] Dinç, Y. (2010). Conjoint Analysis and an Application on the Selection Criteria of Automobile. Master Thesis, Marmara University, Institute of Social Sciences, Department of Statistics, Istanbul, 93 pp.
  • [16] Dölekoğlu, C. Ö. (2002). Consumer Quality Preferences for Products, Attitude of Consumers on Health Risk and Nutritional Information (Adana Case). Unpublished Ph. D. Thesis, Çukurova University, Institute of Natural and Applied Sciences, Adana, 171 pp.
  • [17] Erdoğan, C. (2006). Determining the Consumer Preference of Automobiles with Conjonit Analysis. Master Thesis, Gazi University, Institute of Natural and Applied Sciences, Ankara 75 pp.
  • [18] Filiz, Z. and Şengöz, M. (2010). Kasko Sigortası Tercihinin Konjoint Analizi ile İncelenmesi. “İşGüç” Industrial Relations and Human Resources Journal, 12(1): 107-121.
  • [19] Green, P.E., ve Srinivasan, V., (1978). Conjoint Analysis in Consumer Research :Issues and Outlook, Journal of Consumer Research, 5, 103-123.
  • [20] Gündüz, S., Dölekoğlu, C. Ö., and Say, D. (2019). Sensory Analysis with Goose Consumption Preferences Substitute Products. European Journal of Science and Technology, (16): 32-40.
  • [21] Güner, A., Doğruer, Y., Uçar, G., Yörük, H. D. (2002). Salam Üretiminde Kaz Etinin Kullanılabilme İmkanları. The Turkish Journal of Veterinary and Animal Sciences, 26: 1303-1308.
  • [22] Hair, J. F., Anderson, R., Tatham, R., and Black, W.C. (1992). Multivariate Data Analysis, Third Edition, U.S.A.: Prentice Hall (Higher Education Division, Pearson Education), 480 pp.
  • [23] Kilci, A. E. (2018). Önsöz, Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 11.
  • [24] Kırmızıbayrak, T. (2018). Türkiye’de Kaz Yetiştiriciliğinin Ticari Bir Sektör Olmasının Önündeki Engeller. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 53-68.
  • [25] Kuhfeld, W.F. (2005). Marketing Research Methods in SAS. SAS 9.1 Edition.
  • [26] Li, W., Long, R., Chen, H., Dou, B., Chen, F., Zheng, X., and He, Z. (2020). Public Preference for Electric Vehicle Incentive Policies in China: A Conjoint Analysis. International Journal of Environmental Research and Public Health, 17(1): 318.
  • [27] Liu, B. Y., Wang, Z. Y., Yang, H. M., Wang, J. M., Xu, D., Zhang, R., Wang, Q. (2011). Influence of Rearing System on Growth Performance, Carcass Traits, and Meat Quality of Yangzhou. Poultry Science, 90(3): 653-659.
  • [28] Orme, B. (2010). Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research, 2nd Edition. Madison: Research Publishers LLC.
  • [29] Oz, F., Celik, T., 2015. Proximate Composition, Color and Nutritional Profile of Raw and Cooked Goose Meat with Different Methods. Journal of Food Processing and Preservation, 39: 2442-2454.
  • [30] Poortinga W., Steg, L., Vlek, C., Wiersma, G. (2003). Household Preferences for Energy-Saving Measures: A Conjoint Analysis. Journal of Economic Psychology, 24(1): 49-64.
  • [31] Saatci, M. (2018). Kaz Yetiştirmede Hijyen ve Hastalıklardan Korunma. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 95-109.
  • [32] Şahinkanat, E. (2013). Determination of Consumers’ Purchasing Decisions with Conjoint Analysis. Master Thesis, Uludag University, Social Science Institution, Statistics Department, Bursa, 152 pp.
  • [33] Saraçlı, S. and Şıklar, E. (2005). Examining the Individual Retirement Account with Conjoint Analysis. Journal of Social Sciences, (2): 1-12.
  • [34] Sarıca, M. (2018). Yerli Kazlarımızda Seleksiyonla Verim Artışı Sağlanabilir mi? Bir Uygulama Projesi. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 45-52.
  • [35] Şekeroğlu, A. and Duman, M. (2018). Kaz Ürünleri Pazarlama Yapısı, Mevzuattaki Durum ve Sorunları. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 110-116.
  • [36] Şen, H. and Çemrek, F. (2004). Konjoint Analizi ve Özel Dershane Tercihine Yönelik bir Uygulama. Eskişehir Osmangazi UniversityJournal of Social Sciences, 5(2): 105-120.
  • [37] Sönmez, H. (2006). An Application of Consumer Preferences Via Conjoint Analysis: How to Choose a Home PC. Journal of Social Sciences, 6(2): 185-196.
  • [38] Sönmez, H., (2001). The Usage of Conjoint Analysis in Marketing Research and an Application. Ph.D. Thesis, Anadolu University, Institute of Natural and Applied Sciences, Department of Statistics, Eskişehir, 183 pp.
  • [39] Soykan, Y. (2009). Conjoint Analysis in Industrial Purchasing Decisions and an Application. Akademik Bakış, 16: 1-18.
  • [40] Tatlıdil, H. (2015). Siyasi Lider Profili-Konjoint Analizi Uygulaması. (Basılmamış Notlar).
  • [41] Tekbalkan, M. (2017). The Role of Local and Regional Food in Local Tourism: Sample of Samsun Kaz Tiridi. Journal of Tourism and Gastronomy Studies, 5(4): 155-169.
  • [42] TSI, 2019. Turkish Statistical Institute. www.tuik.gov.tr. Access Date: 10.10.2010.
  • [43] Turanlı, M., Bağdatlı Kalkan, S., and Yazılı, N. (2011). Customers’ Mobile Phone Package Choice and Price Flexibility Teste with Conjoint Analysis. Trakya University Journal of Social Science, 13 (2): 355-370.
  • [44] Turanlı, M., Taşpınar Cengiz, D., and Işık, M. (2013). Konjoint Analizi ile Gazete Tercihlerini Etkileyen Faktörlerin Belirlenmesi. İstanbul Üniversitesi İktisat Fakültesi Ekonometri ve İstatistik Dergisi, (19): 1-26.
  • [45] Yamak, U. S. (2018). Kazlarda Üreme ve Kuluçka. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu. 22-23 February 2018, Yozgat, 69-84.
  • [46] Yavuz, S. and Çemrek, F. (2013). The Determination of Residental Preferences of Healthcare Workers Through Conjoint Analysis. Atatürk University Journal of Graduate School of Social Sciences, 17(2): 379-396.
  • [47] Yıldız, B. and Küçükkancabaş Esen, S. (2020). The Influence of Eco-Labelling on Consumer Behaviors: Examining Refrigerator Eco-Labels Using Conjoint Analysis. Productivity Journal (Verimlilik Dergisi), (1): 83-98.

Year 2020, Volume: 1 Issue: 2, 62 - 75, 31.12.2020

Selim Gündüz

Abstract

Project Number

BAP project No. 18113008

References

  • [1] Aktaş, S., Akkuş, Ö. and Osmanoğlu, S. (2012). A Practical Study on the Performances of the Conditional Logit and Conjoint Analyses in the Modelling of the Polychotomous Dependent Variable. Istanbul Commerce University Journal of Science, 11(21): 25-40.
  • [2] Álvarez-Farizo, B. and Hanley, N. (2002). Using Conjoint Analysis to Quantify Public Preferences over the Environmental Impacts of Wind Farms. An Example from Spain. Energy Policy, 30(2): 107-116.
  • [3] Arslan, C. (2018). Kazların Ekstansif, Yarı Entansif ve Entensif Üretim Sistemlerine Göre Belirlenmesi. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 85-94.
  • [4] Aşkın, Y. and İlaslan, M. (1976). Kars Bölgesi Kazlarında Ekonomik Önemi Olan Bazı Karakterler Üzerinde Araştırmalar. Ankara Üniversitesi Ziraat Fakültesi Yıllığı, 26: 542-552.
  • [5] Baki, F., Saner, G., Adanacıoğlu, H., and Güler, D. (2017). A Conjoint Analysis of Consumer Preferences for Honeydew Honey in Turkey: A Case of İzmir Province. Balkan and Near Eastern Journal of Social Sciences, 3(2): 50-57.
  • [6] Boz, M.A. and Sarıca, M. (2018). Türkiye’de Kaz Yetiştiriciliğinin Durumu ve Geleceği. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 36-44.
  • [7] Bridges, J. F., Hauber, A. B., Marshall, D., Lloyd, A., Prosser, L. A., Regier, D. A., Johnson, F. R., and Mauskopf, J. (2011). Conjoint Analysis Applications in Health a Checklist: A Report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. Value in Health, 14(4): 403-413.
  • [8] Çamlıdere, Ö. (2005). Conjoint Analysis and an Application to Mobile Phones Preference. Master Thesis, Gazi University, Institute of Natural and Applied Sciences, Ankara, 64 pp.
  • [9] Çatpınar, H. (2005). Özel Sağlık Sigortalarında Konjoint Analizi ile Tüketici Tercihi. Sigorta Araştırmaları Dergisi, 1.
  • [10] Çetinel, B. and Yeniay, O. (1997). Konjoint Analiz ve Cep Telefonu Pazarı Üzerine Bir Araştırma. 3. Ulusal Ekonometri ve İstatistik Sempozyumu Bildiri Kitabı, Bursa, 15-24.
  • [11] Çevik, O. and Yiğit, A. M. (2011). Determining Office Furniture Consumers’ Preferences with Conjoint Analysis. Karamanoglu Mehmetbey University Journal of Social and Economic Research, 13 (20): 105-110.
  • [12] Ceylan, H. H. (2013). Market Segmentation Based on Benefit in Retail Sector by Using Conjoint and Cluster Analysis. CBU, Journal of Management and Economics, 20(1): 141-154.
  • [13] Deniz Akıncı, E., Bacanlı, S., and Kıroğlu, G. (2007). Adaptive Conjoint Analysis and an Application on Istanbul Discount Markets. Journal of Dogus University, 8 (1): 1-11.
  • [14] Dikici, T. (2006). Conjoint Analysis and an Application in Connection with Determination of Mobile Phone Preference of Consumers. Master Thesis, Uludag University, Institute of Social Sciences, Econometrics Department, Bursa, 113 pp.
  • [15] Dinç, Y. (2010). Conjoint Analysis and an Application on the Selection Criteria of Automobile. Master Thesis, Marmara University, Institute of Social Sciences, Department of Statistics, Istanbul, 93 pp.
  • [16] Dölekoğlu, C. Ö. (2002). Consumer Quality Preferences for Products, Attitude of Consumers on Health Risk and Nutritional Information (Adana Case). Unpublished Ph. D. Thesis, Çukurova University, Institute of Natural and Applied Sciences, Adana, 171 pp.
  • [17] Erdoğan, C. (2006). Determining the Consumer Preference of Automobiles with Conjonit Analysis. Master Thesis, Gazi University, Institute of Natural and Applied Sciences, Ankara 75 pp.
  • [18] Filiz, Z. and Şengöz, M. (2010). Kasko Sigortası Tercihinin Konjoint Analizi ile İncelenmesi. “İşGüç” Industrial Relations and Human Resources Journal, 12(1): 107-121.
  • [19] Green, P.E., ve Srinivasan, V., (1978). Conjoint Analysis in Consumer Research :Issues and Outlook, Journal of Consumer Research, 5, 103-123.
  • [20] Gündüz, S., Dölekoğlu, C. Ö., and Say, D. (2019). Sensory Analysis with Goose Consumption Preferences Substitute Products. European Journal of Science and Technology, (16): 32-40.
  • [21] Güner, A., Doğruer, Y., Uçar, G., Yörük, H. D. (2002). Salam Üretiminde Kaz Etinin Kullanılabilme İmkanları. The Turkish Journal of Veterinary and Animal Sciences, 26: 1303-1308.
  • [22] Hair, J. F., Anderson, R., Tatham, R., and Black, W.C. (1992). Multivariate Data Analysis, Third Edition, U.S.A.: Prentice Hall (Higher Education Division, Pearson Education), 480 pp.
  • [23] Kilci, A. E. (2018). Önsöz, Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 11.
  • [24] Kırmızıbayrak, T. (2018). Türkiye’de Kaz Yetiştiriciliğinin Ticari Bir Sektör Olmasının Önündeki Engeller. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 53-68.
  • [25] Kuhfeld, W.F. (2005). Marketing Research Methods in SAS. SAS 9.1 Edition.
  • [26] Li, W., Long, R., Chen, H., Dou, B., Chen, F., Zheng, X., and He, Z. (2020). Public Preference for Electric Vehicle Incentive Policies in China: A Conjoint Analysis. International Journal of Environmental Research and Public Health, 17(1): 318.
  • [27] Liu, B. Y., Wang, Z. Y., Yang, H. M., Wang, J. M., Xu, D., Zhang, R., Wang, Q. (2011). Influence of Rearing System on Growth Performance, Carcass Traits, and Meat Quality of Yangzhou. Poultry Science, 90(3): 653-659.
  • [28] Orme, B. (2010). Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research, 2nd Edition. Madison: Research Publishers LLC.
  • [29] Oz, F., Celik, T., 2015. Proximate Composition, Color and Nutritional Profile of Raw and Cooked Goose Meat with Different Methods. Journal of Food Processing and Preservation, 39: 2442-2454.
  • [30] Poortinga W., Steg, L., Vlek, C., Wiersma, G. (2003). Household Preferences for Energy-Saving Measures: A Conjoint Analysis. Journal of Economic Psychology, 24(1): 49-64.
  • [31] Saatci, M. (2018). Kaz Yetiştirmede Hijyen ve Hastalıklardan Korunma. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 95-109.
  • [32] Şahinkanat, E. (2013). Determination of Consumers’ Purchasing Decisions with Conjoint Analysis. Master Thesis, Uludag University, Social Science Institution, Statistics Department, Bursa, 152 pp.
  • [33] Saraçlı, S. and Şıklar, E. (2005). Examining the Individual Retirement Account with Conjoint Analysis. Journal of Social Sciences, (2): 1-12.
  • [34] Sarıca, M. (2018). Yerli Kazlarımızda Seleksiyonla Verim Artışı Sağlanabilir mi? Bir Uygulama Projesi. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 45-52.
  • [35] Şekeroğlu, A. and Duman, M. (2018). Kaz Ürünleri Pazarlama Yapısı, Mevzuattaki Durum ve Sorunları. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu, 22-23 February 2018, Yozgat, 110-116.
  • [36] Şen, H. and Çemrek, F. (2004). Konjoint Analizi ve Özel Dershane Tercihine Yönelik bir Uygulama. Eskişehir Osmangazi UniversityJournal of Social Sciences, 5(2): 105-120.
  • [37] Sönmez, H. (2006). An Application of Consumer Preferences Via Conjoint Analysis: How to Choose a Home PC. Journal of Social Sciences, 6(2): 185-196.
  • [38] Sönmez, H., (2001). The Usage of Conjoint Analysis in Marketing Research and an Application. Ph.D. Thesis, Anadolu University, Institute of Natural and Applied Sciences, Department of Statistics, Eskişehir, 183 pp.
  • [39] Soykan, Y. (2009). Conjoint Analysis in Industrial Purchasing Decisions and an Application. Akademik Bakış, 16: 1-18.
  • [40] Tatlıdil, H. (2015). Siyasi Lider Profili-Konjoint Analizi Uygulaması. (Basılmamış Notlar).
  • [41] Tekbalkan, M. (2017). The Role of Local and Regional Food in Local Tourism: Sample of Samsun Kaz Tiridi. Journal of Tourism and Gastronomy Studies, 5(4): 155-169.
  • [42] TSI, 2019. Turkish Statistical Institute. www.tuik.gov.tr. Access Date: 10.10.2010.
  • [43] Turanlı, M., Bağdatlı Kalkan, S., and Yazılı, N. (2011). Customers’ Mobile Phone Package Choice and Price Flexibility Teste with Conjoint Analysis. Trakya University Journal of Social Science, 13 (2): 355-370.
  • [44] Turanlı, M., Taşpınar Cengiz, D., and Işık, M. (2013). Konjoint Analizi ile Gazete Tercihlerini Etkileyen Faktörlerin Belirlenmesi. İstanbul Üniversitesi İktisat Fakültesi Ekonometri ve İstatistik Dergisi, (19): 1-26.
  • [45] Yamak, U. S. (2018). Kazlarda Üreme ve Kuluçka. Türkiye Kaz Yetiştiriciliği Çalıştayı ve Kaz Günü Etkinliği Sonuç Raporu. 22-23 February 2018, Yozgat, 69-84.
  • [46] Yavuz, S. and Çemrek, F. (2013). The Determination of Residental Preferences of Healthcare Workers Through Conjoint Analysis. Atatürk University Journal of Graduate School of Social Sciences, 17(2): 379-396.
  • [47] Yıldız, B. and Küçükkancabaş Esen, S. (2020). The Influence of Eco-Labelling on Consumer Behaviors: Examining Refrigerator Eco-Labels Using Conjoint Analysis. Productivity Journal (Verimlilik Dergisi), (1): 83-98.
There are 47 citations in total.

Details

Primary Language English
Journal Section Research Articles
Authors

Selim Gündüz 0000-0001-5289-6089

Project Number BAP project No. 18113008
Publication Date December 31, 2020
Submission Date December 22, 2020
Acceptance Date December 30, 2020
Published in Issue Year 2020 Volume: 1 Issue: 2

Cite

APA Gündüz, S. (2020). Determination of Consumer Preferences for Goose Meat Using Conjoint Analysis. NATURENGS, 1(2), 62-75.
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