برآورد تمایل به پرداخت خریداران برای فناوری اطلاعات تغذیه‌ای، مطالعه موردی شهروندان ساری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 عضو هیئت علمی

2 گروه اقتصاد کشاورزی دانشگاه علوم کشاورزی و منابع طبیعی ساری

3 دانشیار اقتصاد کشاورزی دانشگاه تبریز

4 گروه علوم کشاورزی ، غذا و محیط زیست، دانشگاه پلی تکنیک مارچه

چکیده

جامعه سالم زیربنای توسعه هر کشور بوده و یکی از راه‌های نیل به این هدف برخورداری از تغذیه صحیح است. اگر انتخاب و مصرف مواد غذایی به نحو صحیح انجام گیرد مشکل بیش‌خواری و عدم تعادل تغذیه‌ای تا حدود زیادی حل شده و به کاهش هزینه‌های بهداشت عمومی کمک می‌کند. یکی راهکار مهم دادن اطلاعات و هشدارهای لازم به خریداران در هنگام خرید می‌باشد. هدف از این پژوهش شناسایی اهمیت برچسب اطلاعات تغذیه‌ای نزد مصرف‌کنندگان از طریق برآورد تمایل به پرداخت آنان برای فنآوری‌های ارائه‌دهنده اطلاعات تغذیه‌ای است. برای این منظور از مدل لاجیت چند جمله‌ای استفاده گردید. داده‌ها مورد نیاز از طریق طراحی و تکمیل پرسشنامه از 203 پاسخ‌گو از میان شهروندان ساروی در سال 1398 جمع‌آوری شد. نتایج حاصل از برآورد تمایل به پرداخت نشان می‌دهد، بالاترین تمایل به پرداخت مربوط به ویژگی هشدار چربی با مبلغ 23000 تومان و کم‌ترین مربوط به ویژگی سبد با مبلغ 8000 تومان می‌باشد. مثبت شدن تمایل به پرداخت، امکان تحلیل سرمایه‌گذاری برای تکنولوژی اطلاعات تغذیه‌ایی را فراهم می‌کند.

کلیدواژه‌ها


عنوان مقاله [English]

Estimating of Willingness to Pay of Buyers for Nutritional Information Technology, a Case Study of Sari's Citizens

نویسندگان [English]

  • Seyyedehsara Sadrmousavigargari 2
  • Esmaeil Pishbahar 3
  • Raffaele Zanoli 4
2 Department of Agricultural Economics, Sari Agricultural Sciences and Natural Resources University.
3 Associate Professor of Agricultural Economics, University of Tabriz
4 Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University
چکیده [English]

A healthy society is the foundation of development in every country and one way to achieve such a goal is enjoying healthy nutrition. If food is selected and consumed properly, the problems of overeating and lack of nutritional are solved to large extent, helping decreased costs of public health. One important way is to provide information and required alert to a buyer on a shopping trip. The purpose of this study is to identify the importance of label of nutritional information to consumers through estimating their willingness to pay for technologies for providing nutritional information. Multinomial logit is used to get it. The data were collected through designing and filling the survey from 203 respondents from citizens of Sari in 1398. The results of the estimation of willing to pay show fat alert attribute has the highest willing to pay (23000 Tomans) and basket attribute has the lowest willing to pay. The positive willing to pay provides investment analysis for nutritional information technology.

کلیدواژه‌ها [English]

  • Choice experiment
  • Nutrition label
  • nutrition information technology
  • willingness to pay
  • polynomial logit
  1. Statistical Center, National Population and Housing Census of Iran 2016; https://www.amar.org.ir
  2. Johnson R, Orme B. Sample size issues for conjoint analysis. Getting started with conjoint analysis: strategies for product design and pricing research. (2010); Madison: Research Publishers LLC, 57-66.
  3. Lowe B, de Souza-Monteiro DM, Fraser I. Nutritional labelling information: Utilization of new technologies. Journal of Marketing Management, 2013; 29(11-12):1337-1366. [doi:10.1080/0267257X.2013.798673]
  4. Hodgkins C, Barnett J, Wasowicz-Kirylo G, Stysko-Kunkowska M, Gulcan Y, Kustepeli Y, Gibbs M. Understanding how consumers categorise nutritional labels: a consumer derived typology for front-of-pack nutrition labelling. Appetite, 2012; 59(3): 806-817. [doi:10.1016/j.appet.2012.08.014].
  5. Van Camp D, de Souza Monteiro DM, Hooker NH. Stop or go? How is the UK food industry responding to front-of-pack nutrition labels? European Review of Agricultural Economics, 2011; 39(5): 821-842. [doi:10.1093/erae/jbr063]
  6. Grunert KG, Wills JM, Fernández-Celemín L. Nutrition knowledge, and use and understanding of nutrition information on food labels among consumers in the UK. Appetite, 2010; 55(2):177-189. https://jfh.tabriz.iau.ir/article_517068.html
  7. Balcombe K, Fraser I, Di Falco S. Traffic lights and food choice: A choice experiment examining the relationship between nutritional food labels and price. Food policy, 2010; 35(3): 211-220. https://econpapers.repec.org/article/eeejfpoli
  8. De Palma A, Myers GM, Papageorgiou YY. Rational choice under an imperfect ability to choose. The American Economic Review, 1994; 419-440. https://ideas.repec.org/a/aea/aecrev/v84y1994i3p419-40.html
  9. Swait J, Adamowicz W. Choice environment, market complexity, and consumer behavior: a theoretical and empirical approach for incorporating decision complexity into models of consumer choice. Organizational behavior and human decision processes, 2001; 86(2): 141-167. [org/10.1006/obhd.2000.2941
  10. Wansink B, Just DR, Payne CR. Mindless eating and healthy heuristics for the irrational. American Economic Review, 2009; 99(2): 165-69. [DOI: 1257/aer.99.2.165]
  11. Moghaddasi R, Shondi Z, Kiani­Rad A. Labelling of meat and affecting factors on its demand in Tehran, Agricultural Economics and Development, 2013; 21(4): 123-138. [doi:30490/AEAD.2014.58721]
  12. Majzoobi M, Darabzadeh N. Effect of Nutrition Information on Consumer Perception of the Quality of Wheat Germ Cake. Iranian Food Science and Technology Research Journal, 2009; 5(2): 172-180. [doi:10.22067/ifstrj.v5i2.3745]
  13. Ezedean N, Babashafi M. The Role of Traffic Light Labeling Policy in Healthy Food Choices: A review paper. Health Research Journal, 2018; 4 (2): 112-119. https://civilica.com/doc/1516069
  14. Barreiro Hurlé J, Gracia A, DeMagistris T. Does nutrition information on food products lead to healthier food choices? Food Policy, 2010; 35(3): 221-229. [doi:10.1016/j.foodpol.2009.12.006].
  15. Berning JP, Chouinard HH, McCluskey JJ. Do positive nutrition shelf labels affect consumer behavior? Findings from a field experiment with scanner data. American Journal of Agricultural Economics, 2010; 93(2): 364-369. [doi:10.1093/ajae/aaq104]
  16. Balcombe K, Fraser I, Lowe B, Souza Monteiro D. Information customization and food ch American Journal of Agricultural Economics, 2015; 98(1): 54-73. [doi:10.1093/ajae/aav033].
  17. Findling MTG, Werth PM, Musicus AA, Bragg MA, Graham DJ, Elbel B, Roberto CA. Comparing five front-of-pack nutrition labels' influence on consumers' perceptions and purchase intentions. Preventive medicine, 2018; 106: 114-121. [doi:10.1016/j.ypmed.2017.10.022]
  18. Mhurchu CN, Eyles H, Jiang Y, Blakely T. Do nutrition labels influence healthier food choices? Analysis of label viewing behaviour and subsequent food purchases in a labelling intervention trial. Appetite, 2018; 121: 360-365. [doi:10.1016/j.appet.2017.11.105]
  19. Gao Z, Schroeder TC. Effects of label information on consumer willingness-to-pay for food attributes. American Journal of Agricultural Economics, 2009; 91(3): 795-809. https://www.jstor.org/stable/20616236
  20. Chalak A, Abiad M. How effective is information provision in shaping food safety related purchasing decisions? Evidence from a choice experiment in Lebanon. Food quality and preference, 2012; 26(1): 81-92. [doi:10.1016/j.foodqual.2012.04.001]
  21. Breidert C, Hahsler M, Reutterer T. A review of methods for measuring willingness-to-pay. Innovative Marketing, 2006; 2(4): 8-32. https://scholar.google.com/scholar?q=A+review+of+methods+for+measuring+willingness-to-pay+Breidert+2006
  22. Lancaster A New Approach to Consumer Theory. J. Political Econ. 1966; 74, 132–157. http://www.journals.uchicago.edu/doi/10.1086/259131
  23. Thurstone Psychophysical analysis. The American journal of psychology, 1987; 100(3/4): 587-609. https://pubmed.ncbi.nlm.nih.gov/3322058/
  24. McFadden Conditional Logit Analysis of Qualitative Choice Behavior. In Frontiers in Econometrics, ed. P. Zarembka. 1974; (New York: Academic Press). https://eml.berkeley.edu/reprints/mcfadden/zarembka.pdf
  25. Kim JH, Kim HJ, Yoo SH. Willingness to pay for fuel-cell electric vehicles in South Korea. Energy, 2019; 174: 497-502. [DOI: 1016/j.energy.2019.02.185Get rights and content]
  26. Shine A, O’Reilly S, O’Sullivan K. Consumer use of nutrition labels. British Food Journal, 1997; 99(8): 290-296.[ DOI: 1108/00070709710188390]
  27. Van Loo EJ, Caputo V, Nayga RM, Meullenet JF, Ricke SC. Consumers’ willingness to pay for organic chicken breast: Evidence from choice experiment. Food Quality and Preference, 2011; 22(7): 603-613. [DOI:1016/j.foodqual.2011.02.003]
  28. Sobhanian SMH, Ebadi J, Mehrara M. Identifying and evaluating factors influencing the decision of Tehran citizens to enter the family doctor plan; using a discrete choice experiment. Economic Research Journal, 2015; 50(2): 327-357 [DOI:22059/jte.2015.55085]
  29. Zehni K, Rokhzadi MZ. Relationship Between Body Mass Index With Physical Activity and Some of demographic Characteristics among students in Kurdistan university of medical sciences.. SJNMP 2017; 2 (3): 49-57
    http://sjnmp.muk.ac.ir/article-1-98-fa.html
  30. Mirghotbi M, Bazhan M, Amiri Z. Knowledge and Practice of Consumers in Food Labels in Tehran, 2008–2009. Payesh (Health Monitor), 2012; 11(4): 505–510. https://sid.ir/paper/23928/fa
  31. Kordi M, Maleki F, Ravasi A, Satarifard S. Effect of eight weeks high-fat diet with endurance training on plasma levels of Amylin in male Wistar rats. Iran South Med J. 2016; 19 (2): 234-243. http://ismj.bpums.ac.ir/article-1-787-fa.html