IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i5p952-d1133848.html
   My bibliography  Save this article

Optimum Support Policy Component for the Development of Agricultural Production: Potato Producer

Author

Listed:
  • Yavuz Taşcıoğlu

    (Faculty of Agriculture, Department of Agricultural Economics, Akdeniz University, 07059 Antalya, Turkey)

  • Mevlüt Gül

    (Faculty of Agriculture, Department of Agricultural Economics, Isparta University of Applied Sciences, 32200 Isparta, Turkey)

  • Metin Göksel Akpınar

    (Faculty of Agriculture, Department of Agricultural Economics, Akdeniz University, 07059 Antalya, Turkey)

  • Bahri Karlı

    (Faculty of Agriculture, Department of Agricultural Economics, Isparta University of Applied Sciences, 32200 Isparta, Turkey)

  • Bektaş Kadakoğlu

    (Faculty of Agriculture, Department of Agricultural Economics, Isparta University of Applied Sciences, 32200 Isparta, Turkey)

  • Bekir Sıtkı Şirikçi

    (Yozgat Vocational Schools, Department of Finance, Banking and Insurance, Yozgat Bozok University, 66100 Yozgat, Turkey)

  • Musa Acar

    (Eskil Vocational School, Aksaray University, 68800 Aksaray, Turkey)

  • Hilal Yılmaz

    (Eastern Mediterranean Agricultural Research Institute Directorate, 01375 Adana, Turkey)

Abstract

The present study aimed to determine the optimum policy component in an example of potato cultivation development based on the principle of the efficient use of scarce resources and maximizing the benefit of the producer. Agricultural support policies are commonly implemented by adopting a top-down approach. Regarding benefit maximization at the target group level, policies for agricultural products should be determined with a bottom-up approach. In this manner, in the present study, potato producers were determined to be the target group. Therefore, this study investigated the policy component that provides the highest benefit in line with the demands, expectations, and tendencies of the target group. The micro-data obtained from the potato-growing enterprises operating in provinces where potato cultivation was intensively carried out within the scope of Turkey constituted the research data. A face-to-face survey technique was used as the method for collecting the producer data. Simple descriptive statistics and one of the multivariate analysis techniques, conjoint analysis, were applied in the analysis and evaluation of the data. The optimum policy component setup was determined to be “Price and Payment Support: Above Market Price and 2 months term, Support Area and Amount: to production, 25.47 USD/da (23.04 EUR/da), time of announcement for the supports: pre-planting, and producer’s declaration: I do (I declare)” for the potato product. Accordingly, the necessity of a bottom-up approach in the planning and implementation of an agricultural support policy in Turkey is explained based on the results obtained. Therefore, it is considered necessary and beneficial to measure the level of producer benefits on the focus of applications that encourage potato production.

Suggested Citation

  • Yavuz Taşcıoğlu & Mevlüt Gül & Metin Göksel Akpınar & Bahri Karlı & Bektaş Kadakoğlu & Bekir Sıtkı Şirikçi & Musa Acar & Hilal Yılmaz, 2023. "Optimum Support Policy Component for the Development of Agricultural Production: Potato Producer," Agriculture, MDPI, vol. 13(5), pages 1-13, April.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:5:p:952-:d:1133848
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/5/952/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/5/952/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lazarus, Sheryl S. & White, Gerald B., 1984. "Economic Impact Of Introducing Rotations On Long Island Potato Farms," Northeastern Journal of Agricultural and Resource Economics, Northeastern Agricultural and Resource Economics Association, vol. 13(2), pages 1-8, October.
    2. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Winfried Steiner & Harald Hruschka, 2002. "A Probabilistic One-Step Approach to the Optimal Product Line Design Problem Using Conjoint and Cost Data," Review of Marketing Science Working Papers 1-4-1003, Berkeley Electronic Press.
    2. Merja Halme & Kari Linden & Kimmo Kääriä, 2009. "Patients’ Preferences for Generic and Branded Over-the-Counter Medicines," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 2(4), pages 243-255, December.
    3. Dufhues, T. & Buchenrieder, G., 2004. "Der Beitrag der Conjoint Analyse zur nachfrageorintierten Entwicklung des ländlichen Finanzsektors in Vietnam," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 39.
    4. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    5. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    6. Mahesh Balan U & Saji K. Mathew, 2021. "Personalize, Summarize or Let them Read? A Study on Online Word of Mouth Strategies and Consumer Decision Process," Information Systems Frontiers, Springer, vol. 23(3), pages 627-647, June.
    7. Shin, Jungwoo & Hwang, Won-Sik, 2017. "Consumer preference and willingness to pay for a renewable fuel standard (RFS) policy: Focusing on ex-ante market analysis and segmentation," Energy Policy, Elsevier, vol. 106(C), pages 32-40.
    8. Haaijer, Marinus E., 1996. "Predictions in conjoint choice experiments : the x-factor probit model," Research Report 96B22, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    9. Ha, Jinkyung, 2018. "Consumer valuation of Fintech: The case of Mobile Payment in Korea," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society 190341, International Telecommunications Society (ITS).
    10. P. A. Ferrari & S. Salini, 2008. "Measuring Service Quality: The Opinion of Europeans about Utilities," Working Papers 2008.36, Fondazione Eni Enrico Mattei.
    11. Steinhorst, M.P. & Bahrs, E., 2013. "Renditansprüche im Kontext gleichmäßiger Rückflüsse – Ergebnisse eines Experiments mit Stakeholdern des Agribusiness," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 48, March.
    12. Luisa Menapace & Gregory Colson & Carola Grebitus & Maria Facendola, 2011. "Consumers' preferences for geographical origin labels: evidence from the Canadian olive oil market," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 38(2), pages 193-212, June.
    13. Srinivasan, V. Seenu & Netzer, Oded, 2007. "Adaptive Self-Explication of Multi-attribute Preferences," Research Papers 1979, Stanford University, Graduate School of Business.
    14. Fusco, Elisa, 2023. "Potential improvements approach in composite indicators construction: The Multi-directional Benefit of the Doubt model," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    15. Xue, Hong & Mainville, Denise Y. & You, Wen & Nayga, Rodolfo M., Jr., 2009. "Nutrition Knowledge, Sensory Characteristics and Consumers’ Willingness to Pay for Pasture-Fed Beef," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49277, Agricultural and Applied Economics Association.
    16. Barbara Baarsma, 2003. "The Valuation of the IJmeer Nature Reserve using Conjoint Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 25(3), pages 343-356, July.
    17. Robert S. Wigton & Vincent L. Hoellerich & Kashinath D. Patil, 1986. "How Physicians Use Clinical Information in Diagnosing Pulmonary Embolism," Medical Decision Making, , vol. 6(1), pages 2-11, February.
    18. Kowalska-Pyzalska, Anna & Michalski, Rafał & Kott, Marek & Skowrońska-Szmer, Anna & Kott, Joanna, 2022. "Consumer preferences towards alternative fuel vehicles. Results from the conjoint analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    19. Emmanuel Olateju Oyatoye & Sulaimon Olanrewaju Adebiyi & Bilqis Bolanle Amole, 2013. "An Application of Conjoint Analysis to Consumer Preference for Beverage Products in Nigeria," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(6), pages 43-56, December.
    20. Kim, Junghun & Seung, Hyunchan & Lee, Jongsu & Ahn, Joongha, 2020. "Asymmetric preference and loss aversion for electric vehicles: The reference-dependent choice model capturing different preference directions," Energy Economics, Elsevier, vol. 86(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2023:i:5:p:952-:d:1133848. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.