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研究生:邱楷涵
研究生(外文):Kai-Han Qiu
論文名稱:大臺北地區消費者對純米米粉的購買行為與願付價值之研究
論文名稱(外文):The Analysis of Consumers’ Behavior and Willingness to Pay for Pure Rice Noodles in Great Taipei Area
指導教授:陳郁蕙陳郁蕙引用關係
指導教授(外文):Yu-Hui Chen
口試委員:劉鋼李俊鴻詹滿色
口試委員(外文):Kang LiuChun-Hung LeeMan-ser Jan
口試日期:2017-05-27
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:農業經濟學研究所
學門:農業科學學門
學類:農業經濟及推廣學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:112
中文關鍵詞:純米米粉選擇模型願付價格羅吉斯模型
外文關鍵詞:pure rice noodleschoice modelwillingness to paylogit model
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在2013年爆發米粉產品標示不實事件,多數市售米粉產品標示的含米量比例和實際情況有差距,引起社會大眾關注到米粉是否含有米的問題,食品藥物管理署在標示不實事件後對米粉產品的品名進行規範,並允許業者在包裝上加入「地方冠名」的標示,純米米粉也因為食品安全事件受到消費者注意,且因為品名規範而和其他米粉產品產生區別,因此本研究欲瞭解消費者對純米米粉的願付價值及米粉產品的購買行為,使用選擇模型衡量米粉產品之屬性與水準的偏好。本研究於2017年3月在臺北市舉辦4場實驗,招募128位大臺北地區的消費者,在實驗中設計參與者盲測試吃三種不同含米量比例的米粉產品,試吃後公布答案及提供含米量比例的訊息,並於實驗前後各進行一次米粉產品的方案選擇。

實證結果顯示,經集群分析可依消費者對米粉產品的認知與影響購買因素的重要性程度,分為「多元並重」、「不重視純米米粉」與「重視純米米粉」三群,「多元並重」及「重視純米米粉」的消費群較「不重視純米米粉」的消費群平均年齡高,且較注重產品上的標示。本研究在選擇模型的評估上,使用MNL和RPL模型進行分析,結果顯示實驗前後消費者最偏好的產品方案為具地方冠名、無食品添加劑的純米米粉,在各水準的影響上,消費者對純米米粉、地方冠名具有正向顯著偏好,對價格、添加食品添加劑為負向顯著偏好,而實驗會加強消費者者對於純米米粉、無添加食品添加劑的願付價值。在LCM模型的分群分析上,結果顯示不同組別在屬性偏好上具有差異性,而顯著變數之影響偏好的情況和MNL及RPL一致。

綜上所述,消費者對地方冠名具正向偏好,表示「新竹米粉」的品名會對消費者在選擇產品上造成影響,因此政府單位在規劃放寬米粉產品品名的標準上,應當謹慎評估,以減少對純米米粉業者的衝擊。此外,業者若能提供消費者試吃不同含米量比例之米粉產品,將可促進消費者購買純米米粉,可作為產品行銷策略的參考。
The mislabeling of rice noodles in 2013 indicated that the proportion of rice content was mislabeled in most rice noodles in the market, that had raised public attention about whether rice noodles contained rice or not. After this incident, a new naming regulation of rice noodles was made by Food and Drug Administration (FDA), which also allowed manufacturers to label the products with “local name rice noodles”. Due to this regulation, rice noodles made of pure rice were distinguished from other fake products. Therefore, this thesis studies the willingness to pay (WTP) of the consumers and their purchasing behavior of pure rice noodles. The choice model is used to estimate the attributes and levels of rice noodles products. We recruited 128 consumers who live in great Taipei area to participate in four experiments in March, 2017. The experiments are designed with a blind test for participants to taste three different kinds of rice noodles, each of which contains different proportions of rice; the answer is revealed afterwards. The choice model is given both before and after the experiments.

The results of cluster analysis and market segmentation model show that the consumers can be categorized into three different groups based on their cognitive situation of rice noodles: “consumers emphasizing on all factors”, “consumers emphasizing on pure rice noodles only”, and “consumers who don’t emphasize on pure rice noodles”. The data shows that the average age of consumers from the first and second group are relatively high comparing to the third. And meanwhile, they pay more attention to the labels of food products.

Multinomial logit model (MNL) and random parameter logit model (RPL) were used to estimate the choice model. First, the results from the choice model suggest that both before and after the experiment, consumers prefer the pure rice noodles that have “local name rice noodles” and are additive-free. Second, the preference is found to be significantly positively correlated with pure rice noodles and “local name rice noodles”, but significantly negatively correlated with food additives and price. Moreover, the experiment can increase the WTP for pure rice noodles and products without food additives. We also use latent class model (LCM). The result from LCM shows that two consumer groups have different preference of levels, and the influence of levels for preference is the same as MNL and RPL.

To sum up, consumers prefer “local name rice noodles”. This means the label of “Hsinchu rice noodles” would influence consumers’ purchasing choice. Therefore, before planning to loosen regulations of the naming of rice noodles, the government should carefully assess the impact on manufacturers of pure rice noodles. In addition, manufacturers of pure rice noodles could provide consumers with chances to taste samples of rice noodles with different proportions of rice content. This can encourage consumers to purchase pure rice noodles and serve as a marketing strategy.
謝辭 i
摘要 ii
Abstract iii
目錄 v
圖目錄 vii
表目錄 viii
第一章、緒論 1
第一節 研究動機與目的 1
第二節 研究步驟 3
第二章、米粉的產業概況 5
第一節 台灣米粉產業發展沿革與概況 5
第二節 彰化縣芬園鄉楓坑村米粉產業概況 6
第三節 新竹米粉產業發展沿革與概況 6
第四節 玉米澱粉使用之原因 8
第五節 純米米粉、調合米粉及炊粉或水粉之差異 9
第六節 米粉食品安全事件及後續影響 11
第七節 小結 14
第三章、文獻回顧 15
第一節 米粉產業相關文獻 15
第二節 米粉之食品科學相關文獻 16
第三節 食品安全相關文獻 17
第四節 聯合分析法相關文獻 20
第五節 選擇模型相關文獻 23
第六節 小結 29
第四章 研究方法論 31
第一節 分析方法 31
第二節 市場區隔理論 34
第三節 選擇模型之研究流程 35
第四節 選擇模型之理論與分析方法 37
第五節 小結 43
第五章、實驗招募與調查 45
第一節 參與者招募與焦點團體 45
第二節 米粉產品的屬性選擇 48
第三節 實驗設計 50
第六章、問卷調查與統計分析 53
第一節 問卷設計 53
第二節 敘述統計分析 56
第七章 實證結果分析 69
第一節 集群分析及市場區隔分析 69
第二節 選擇模型之實證結果 81
第八章 結論與建議 95
第一節 結論 95
第二節 建議 98
參考文獻 100
附錄 111
中國民國國家標準(2013)。CNS11172米粉絲(條)。取自http://www.cnsonline.com.tw/
內政部戶政司(2016)。各縣市十五歲以上現住人口數按性別、年齡及教育程度分布表。取自sowf.moi.gov.tw/stat/gender/ps03-15.xls
毛碧琦、敖長林、焦揚、高琴、劉玉星(2017)。基於選擇實驗的三江平原濕地生態系統服務功能價值評價及偏好異質性研究,生態學報,第37卷第4期,1297-1308。
王文娟(2010)。彰化縣芬園鄉楓坑村米粉產業變遷與發展之探討。大葉大學設計暨藝術學院碩士在職專班碩士論文。
王若文(1997)。自製與市售米粉絲之理化特性及抗解澱粉生成差異性之探討。國立中興大學食品科學研究所碩士論文。
王祥斌(2012)。臺北地區市售米濕製品(米粉、蘿蔔糕、碗粿、米苔目、粄條)中防腐劑與微生物含量調查。國立臺灣海洋大學食品科學研究所碩士論文。
王燕華、劉重善、柯永輝、葉名軒、陳惠珒(2016)。「新竹米粉」怎麼被大陸山寨貨搶名了?。聯合報。取自http://a.udn.com/focus/2016/06/15/22156/index.html
甘志展、李明聰(2008)。消費者對食品安全議題之風險認知與其消息來源可靠度之研究。食品市場資訊,第97卷,第4期,1-10。
朱芳妮、張金鶚、陳淑美(2008)。已購屋者及購屋搜尋者之購屋需求決策比較分析-兼論顯示性偏好及敘述性偏好之差異。都市與計劃,第三十五卷,第四期,339-359。
江伯源(2002)。米粉絲的製作技術-磨粉方法與澱粉添加對產品性質的影響。國立臺灣大學食品科技研究所博士論文。
吳忠君(1997)。多項羅吉特模型設定誤差檢定方法之比較--蒙第卡羅模擬分析。國立中央大學產業經濟學研究所碩士論文。
吳明隆(2011)。SPSS統計應用學習實務:問卷分析與應用統計。台北市:易習。
吳金益(2014)。新竹米粉產業的創新研究。國立交通大學理學院科技與數位學習學程碩士論文。
宋鴻宜(2015)。多元米食推廣情形。農政與農情,第281期,6-11。
李佩倢(2016)。台灣六都消費者對營養補充劑飲品的消費行為與願付價格之研究。國立臺灣大學農業經濟學研究所碩士論文。
李佩隃(2011)。潛在類別分析與二階段群集分析分群效果之比較研究。國立臺灣師範大學教育心理與輔導學研究所碩士論文。
李柏憲(2011)。大台北地區消費者對台灣珍豬品牌豬肉之認知與購買意願。國立台灣大學農業經濟研究所碩士論文。
汪文豪(2013)。開米粉界沒有說的秘密–9成米粉充斥廉價玉米澱粉。上下游News&Market。取自https://www.newsmarket.com.tw/blog/23881/
汪文豪(2014)。含米量25%即可稱米粉? 竹市府將推產地標章。上下游News&Market。取自https://www.newsmarket.com.tw/blog/53069/
周美伶(2005)。購屋者外部資訊搜尋管道選擇行為與搜尋期間之探討,住宅學報,第14卷,第2期,1-25。
周佳蓉、陳國勝(2011)。民眾對食品添加物的認知、知覺風險及風險減輕策略研究,休閒保健期刊,第3期,115-126
林家瑩(2015)。食品安全風險預防之法治化研究。國立臺灣大學法律學研究所碩士論文。
林惠清(2009)。台灣產地國標籤之經濟分析:實驗拍賣法。國立中正大學國際經濟學研究所碩士論文。
林震岩(2006)。多變量分析:SPSS的操作與應用。臺北市:智勝文化。 
邱文聰(2013)。畫餅充飢的食品安全風險管控策略-簡評食品衛生管理法修正。台灣法學雜誌,第238期,11-17。
邱文聰(2015)。從迷失的身分重新找尋食品攙偽假冒管制的可能途徑—以食品身分標準為分析焦點。政大法學評論,第141期,1-49。
洪嘉珮(2010)。應用實驗拍賣評估產地國標示的經濟效益:以茶葉為例。國立中正大學國際經濟學研究所碩士論文。
紀嘉祐(2016)。食品安全的內控機制與企業社會責任之研究。國立中興大學法學系在職專班碩士論文。
范振家(1988)。米粉中添加甘藷澱粉所製得擠壓產品理化性質之探討。國立台灣大學食品科技研究所碩士論文。
袁淑湄(2003)。應用混合Logit模型探討台灣家戶住宅選擇之研究。國立成功大學都市計劃學系研究所碩士論文。
康照洲(2011)。起雲劑中惡意添加塑化劑事件【食品藥物管理局】。取自http://www.fda.gov.tw/tc/includes/SiteListGetFile.ashx?mid=133&id=5048&chk=9a58ee90-6e35-44eb-b26e-a33a726835bd
郭冠吟(2012)。新竹市米粉寮產業文化及聚落空間轉變之研究。中原大學建築設計學系碩士論文。
郭為揚(2004)。米粉製程之衛生安全研究。中國文化大學生活應用科學研究所在職專班碩士論文。
陳佳蓉、陳國勝(2010)。民眾對食品添加物的認知、知覺風險及風險減輕策略研究。休閒保健期刊,115-126。
陳凱莉(2005)。創業導向對傳統產業經營績效之影響—以新竹米粉製造業為例。中華大學科技管理研究所碩士論文。
曾喜鵬、薛立敏(2005)。不同類型遷移者之住宅區位與權屬選擇的實證估計-以台北都會區遷入者為例。台灣土地研究,第八卷,第二期,21-48。
須文宏(1989)。以擠壓技術生產米粉絲。國立臺灣大學食品科技研究所碩士論文。
黃旺成(1976)。台灣省新竹縣志卷三土地志(103頁)。新竹縣:新竹縣文獻委員會。
黃明山(2015)。論食品安全危害與食品標示不實之法律責任-以刑事罰為中心。中央警察大學法律學研究所碩士論文。
黃紀、王德育(2012)。質變數與受限依變數的迴歸分析,臺灣:五南,236-238。
新竹米粉摃丸公會(2017)。米粉摃丸公會聯合網。上網日期:2017年5 月15日,取自 http://www.hc-food.org.tw/
種籽文化工作室(1998)。新竹米粉產業史(31-69頁)。新竹市:新竹市立文化中心。
劉慧瑛、黃菊美、朱戬良(1995)。省產米加工品之成分比較。農特產品加工研討會專刊,209-222。
蔡弘聰(2014)。天字第一號營養師開講(六)談100%純在來米製造的米粉。台灣優良農產品季刊,第44期,16-19。
衛生福利部食品藥物管理署(2013)。澄清今日媒體報導「不實標示傷心 風險如何分級」。取自http://www.fda.gov.tw/TC/newsContent.aspx?id=10486&chk=ad3d6aca-088c-43c3-a9cb-63dc7e8a240e#.WLWcCm997IU
衛生福利部食品藥物管理署(2015)。米粉規定只撐了半天?。取自http://www.fda.gov.tw/TC/newsContent.aspx?id=18177&chk=69cc8e7d-4fee-4653-aff1-b1b93f681f45#.WBLM_y197IU
衛生福利部食品藥物管理署(2016)。市售包裝米粉絲產品標示規定問答集。
蕭文龍(2014)。多變量分析最佳入門實用書:SPSS+LISREL。臺北市:碁峰。
蕭文龍(2016)。統計分析入門與應用:SPSS中文版+SmartPLS 3 (PLS_SEM)。臺北市:碁峰。
賴淑敏、蔣龍祥(2016)。政策大轉彎 "炊粉"可望改名回"米粉"。公視新聞網。取自http://news.pts.org.tw/article/341586
Alfnes, F., Guttormsen, A. G., Steine, G., & Kolstad, K. (2006). Consumers'' willingness to pay for the color of salmon: a choice experiment with real economic incentives. American Journal of Agricultural Economics, 88(4), 1050-1061.
Aoki, K., Akai, K., & Ujiie, K. (2017). A choice experiment to compare preferences for rice in Thailand and Japan: the impact of origin, sustainability, and taste. Food Quality and Preference, 56(Part B), 274-284.
Ares, G., & Deliza, R. (2010). Studying the influence of package shape and colour on consumer expectations of milk desserts using word association and conjoint analysis. Food Quality and Preference, 21(8), 930-937.
Asioli, D., Naes, T., Granli, B. S., & Almli, V. L. (2014). Consumer preferences for iced coffee determined by conjoint analysis: an exploratory study with Norwegian consumers. International Journal of Food Science & Technology, 49(6), 1565-1571.
Baker, G. A. & Burnham T. (2001). Consumer response to genetically modified foods: market segment analysis and implications for producers and policy makers. Journal of Agricultural and Resource Economics, 26 , 387–403.
Balcombe, K., Bitzios, M., Fraser, I., & Haddock-Fraser, J. (2014). Using attribute importance rankings within discrete choice experiments: an application to valuing bread attributes. Journal of Agricultural Economics, 65(2), 446-462.
Bech, M. & Gyrd-Hansen, D. (2005). Effects coding in discrete choice experiments. Health Economics , 14(10), 1079-1083.
Bechtold, K. B., & Abdulai, A. (2014). Combining attitudinal statements with choice experiments to analyze preference heterogeneity for functional dairy products. Food Policy, 47, 97-106.
Bhat, C. R. (1995). A heteroscedastic extreme value model of intercity travel mode choice. Transportation Research Part B: Methodological, 29(6), 471-483.
Bhat, C. R. (1997). An endogenous segmentation mode choice model with an application to intercity travel. Transportation Science, 31(1), 34-48.
Bhattacharya, M, Zee, S. Y., & Corke, H.(1999). Physicochemical properties related to quality of rice noodles. Cereal Chem, 76(6):861–867
Boone, L. E., & Kurtz, D. L. (2005). Contemporary marketing, MA: South-Western College Publications.
Boxall, P. C., & Adamowicz, W. L. (2002). Understanding heterogeneous preferences in random utility models: a latent class Approach. Environmental and Resource Economics, 23(4), 421-446.
Breidert, C.,Hahsler, M., & Reutterer, T. (2006). A review of methods for measuring willingness-to-pay. Innovative Marketing, 2, 1-32.
Carlsson, F., Frykblom, P., & Lagerkvist, C. J. (2007). Consumer benefits of labels and bans on GM foods—choice experiments with swedish consumers. American Journal of Agricultural Economics, 89(1), 152-161.
Chalak, A., & Abiad, M. (2012). How effective is information provision in shaping food safety related purchasing decisions? Evidence from a choice experiment in Lebanon. Food Quality and Preference, 26(1), 81-92.
Choi, A. S., Ritchie, B. W., Papandrea, F., & Bennett, J. (2010). Economic valuation of cultural heritage sites: a choice modeling approach. Tourism Management, 31(2), 213-220.
Clark, M. D., Higgins, R., Gumber, A., Moro, D., Leech, D., Szczepura, A., Dada, S. & West, N. (2013). A better way to measure choices'' discrete choice experiment and conjoint analysis studies in nephrology: a literature review. EMJ Nephrology, 1, 52-59.
Darby, K., Batte, M. T., Ernst, S., & Roe, B. (2008). Decomposing local: a conjoint analysis of locally produced foods. American Journal of Agricultural Economics, 90(2), 476-486.
Dosman, D. M., Adamowicz, W. L., & Hrudey, S. E.(2001). Socioeconomic determinants of health- and food safety-related risk perceptions. Risk Analysis , 21, 307-318
Endrizzi, I., Torri, L., Corollaro, M. L., Demattè, M. L., Aprea, E., Charles, M., Biasioli, F. ,& Gasperi, F.(2015). A conjoint study on apple acceptability: Sensory characteristics and nutritional information. Food Quality and Preference, 40, 39-48.
Erdem, S. (2015). Consumers'' preferences for nanotechnology in food packaging: a discrete choice experiment. Journal of Agricultural Economics, 66(2), 259-279.
Gadioli, I. L., Lacerda de Oliveira Pineli, L. d., Silva Quintiliano Rodrigues, J. d., Bezerra Campos, A., Queiroz Gerolim, I., & Chiarello, M. D. (2013). Evaluation of packing attributes of orange juice on consumers'' intention to purchase by conjoint analysis and consumer attitudes expectation. Journal of Sensory Studies, 28(1), 57-65.
Garrod, G., & Willis, K. G.(1999). Economic valuation of the environment. Northampton: Edward Elgar.
Gineo, W. M .(1990). A conjoint/logit analysis of nursery stock purchases. Northeastern Journal of Agricultural & Resource Economics, 19, 49–58.
Gracia, A., Loureiro, M. L., & Nayga, R. M. (2009). Consumers'' valuation of nutritional information: a choice experiment study. Food Quality and Preference, 20(7), 463-471.
Green, P. E. & Srinivasan, V.(1978). Conjoint analysis in consumer research: issues and outlook. Journal of Consumer Research, 5(2), 103–123.
Green, P. E., & Krieger, A. M.(1991). Product design strategies for target-market positioning. Journal of Product Innovation Management, 8(3), 189–202.
Green, P. E., Krieger, A. M., & Wind, Y. (2001). Thirty years of conjoint analysis: Reflection and prospects .Interfaces, 31(3), S56–S73.
Greene, W. H. (2002). LIMDEP version 8.0 reference guide. Australia: Econometric Software Inc.
Greene, W. H., Hensher, D. A., & Rose, J. (2006). Accounting for heterogeneity in the variance of unobserved effects in mixed logit models. Transportation Research Part B, 40(1), 75-92.
Haddad, Y., Haddad, J., Olabi, A., Shuayto, N., Haddad, T., & Toufeili, I. (2007).Mapping determinants of purchase intent of concentrated yogurt (Labneh) by conjoint analysis. Food Quality and Preference 18(5), 795–802 
Hanley, N., Mourato, S., & Wright, R. E. (2001). Choice modelling approaches: a superior alternative for environmental valuatioin? Journal of Economic Surveys, 15(3), 435-462.
Hanley, N., Wright, R. E., & Koop, G. (2002). Modelling recreation demand using choice experiments: climbing in Scotland. Environmental and resource Economics, 22(3), 449-466.
Hausman, J.& McFadden, D.(1984). A specification test for the multinomial logit model. Ecomometrica, 52, 1219-1240.
Huang, C. L. & Fu, J. (1995). Conjoint analysis of consumer preferences and evaluations of a processed meat. Journal of International Food & Agribusiness Marketing, 7: 35-53.
James, S., & Burton, M. (2003). Consumer preferences for GM food and other attributes of the food system. The Australian Journal of Agricultural and Resource Economics, 47(4), 501–518.
Jan, M. -S., Fu, T. -T, & Huang, C. L.(2007). A conjoint/logit analysis of consumers’ responses to genetically modified tofu in Taiwan. Journal of Agricultural Economics, 58(2), 330-347.
Jervis, M. G., Jervis, S. M., Guthrie, B., & Drake, M. A. (2014). Determining children''s perceptions, opinions and attitudes for sliced sandwich breads. Journal of Sensory Studies, 29(5), 351-361.
Jones, S., & Hensher, D. A.. (2004). Predicting firm financial distress: A Mixed Logit Model. Accounting Review, 79(4) , 1011-1038.
Juutinen, A., Mitani, Y., Mantymaa, E., Shoji, Y., Siikamaki, P., & Svento, R. (2011). Combining ecological and recreational aspects in national park management: a choice experiment application. Ecological Economics, 70(6), 1231-1239.
Kaiser, H. J. (1974). An index of factorial simplicity. Psychometrika,.39(1), 31-36.
Kimura, A., Kuwazawa, S., Wada, Y., Kyutoku, Y., Okamoto, M., Yamaguchi, Y., Masuda, T.; & Dan, I. (2011). Conjoint analysis on the purchase intent for traditional fermented soy product (natto) among Japanese housewives. Journal of Food Science, 76(3), 217-224.
Kotler, P. (1991). Marketing management: analysis, planning, implementation, and control. London: Prentice-Hall International.
Kotler, P., & Armstrong, G. (1991). Principles of marketing. englewood cliffs, N.J.: Prentice Hall International.
Lancaster, K. J. (1996). A new approach to consumer theory. Journal of Political Economy, 74(2), 132-157.
Lessig, V.P. (1972). Market segmentation : theory and research. Journal of Business Administration, 3(2), 69-76.
Liker, B., Stirn, L. Z., Bučar, D. G., & Hrovatin, J. (2016). Examination of decision factors in the process of buying kitchen furniture using conjoint analysis. Wood Industry / Drvna Industrija., 67(2), 141-147.
Lombardi, G. V., Berni, R., & Rocchi, B. (2017). Environmental friendly food. Choice experiment to assess consumer''s attitude toward “climate neutral” milk: the role of communication. Journal of Cleaner Production, 142, 257-262.
Louviere, J. J., & Hensher, D. A. (1982). On the design and analysis of simulated choice or allocation experiments in travel choice modelling. Transportation Research Record, 890, 11–17.
Louviere, J. J., & Woodworth, G. (1983). Design and analysis of simulated consumer choice and allocation experiments: a method based on aggregate data. Journal of Marketing Research, 20, 350-367.
Lusk, J. L., Moore, M., House, L. O., & Morrow, B. (2002). Influence of brand name and type of modification on consumer acceptance of genetically engineered corn chips: a preliminary analysis. The International Food and Agribusiness Management Review, 4(4), 373-383.
McCarthy, J. E., 1981. Basic Marketing: A Managerial Approach 7th ed. Haomewood , Illinois:Richard D. Irwin Inc.
McFadden, D. (1974). The measurement of urban travel demand. Journal of Public Economics, 3, 303-328.
McFadden, D.(1973). Conditional logit analysis of qualitative choice behavior. in: P.Zarembka(Ed) Frontiers in Econometrics(New York: Academic Press),105-142.
McFadden, D., & Train, K. (2000). Mixed MNL models for discrete response. Journal of Applied Econometrics, 15(5), 447-470.
Mesias, F. J., Martinez-Carrasco, F., Martinez, J. M., & Gaspar, P. (2011). Functional and organic eggs as an alternative to conventional production: a conjoint analysis of consumers'' preferences. Journal of the Science of Food and Agriculture, 91(3), 532-538.
Murphy, M., Cowan, C., Meehan, H., & O''Reilly, S. (2004). A conjoint analysis of irish consumer preferences for farmhouse cheese. British Food Journal, 106(4), 288-300.
Nunnally, J. C. (1978). Psychometric Theory, New York: McGraw-Hill.
Olesen, I., Alfnes, F., Røra, M. B., & Kolstad, K. (2010). Eliciting consumers'' willingness to pay for organic and welfare-labelled salmon in a non-hypothetical choice experiment. Livestock Science, 127(2), 218-226.
Pedhazur, E. J. (1997). Multiple regression in behavioral research: explanation and prediction (3rdEd.). New York: Holt, Rinehart and Winston.
Probst, L., Houedjofonon, E., Ayerakwa, H. M., & Haas, R. (2012). Will they buy it? The potential for marketing organic vegetables in the food vending sector to strengthen vegetable safety: a choice experiment study in three West African cities. Food Policy, 37(3), 296-308.
Sælen, H., & Ericson, T. (2013). The recreational value of different winter conditions in Oslo forests: A choice experiment. Journal of Environmental Management, 131, 426-434.
Skreli, E., & Imami, D. (2012). Analyzing consumers’ preferences for apple attributes in Tirana, Albania. International Food and Agribusiness Management Review, 15(4): 137–156.
Stevens, E. B., & Jason, L. A. (2015). Evaluating alcoholics anonymous sponsor attributes using conjoint analysis. Addictive Behaviors, 51, 12-17. 
Train, K., (2002). Discrete choice methods with simulation. Cambridge, U.K: Cambridge University Press.
Train, K. E. (2009). Discrete choice methods with simulation, 2nd ed. Cambridge, UK: Cambridge University Press.
Van Loo, E. J., Caputo, V., Nayga Jr, R. M., Meullenet, J.-F., & Ricke, S. C. (2011). Consumers’ willingness to pay for organic chicken breast: Evidence from choice experiment. Food Quality and Preference, 22(7), 603-613.
Wells, W. D., & Prensky, D. (1996). Consumer behavior, NY: John Wiley and Sons Inc.
Wirth, F. F. (2014). Consumers'' shrimp purchasing preferences: an application of conjoint analysis. Journal of Food Products Marketing, 20(2), 182-195.
Wittink, D. R., & Cattin, P. (1989). Commercial use of conjoint analysis: an update. Journal of Marketing, 53(3), 91-96.
Yang, H.-S., & Kim, C.-S.(2010). Quality characteristics of rice noodle in Korean market . Journal of the Korean Society of Food Science and Nutrition , 39 , 737-744.
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