IDEAS home Printed from https://ideas.repec.org/a/beo/journl/v55y2010i187p87-108.html
   My bibliography  Save this article

Milk Marketing Under Cooperative And Non-Cooperative Marketing Channels: Evidence From West Bengal

Author

Listed:
  • Debnarayan Sarker
  • Bikash Kumar Ghosh

Abstract

The present study is an attempt to empirically investigate the price spread, marketing costs, marketing margins, marketing efficiency, and profit efficiency among market middlemen under cooperative and non-cooperative marketing channels in the domestic trade market of liquid milk in West Bengal. One of the important findings of this study is that, although the inter-market (and intra-market) price variation for liquid milk under the cooperative marketing agency in not far from uniformity, and all marketing agencies under cooperative channels receive much lower abnormal profit per unit of milk as compared with non-cooperative channels, the former fails to provide much economic benefit, either to the producer or to the consumer, because of the burden of much higher fixed cost per unit of liquid milk.

Suggested Citation

  • Debnarayan Sarker & Bikash Kumar Ghosh, 2010. "Milk Marketing Under Cooperative And Non-Cooperative Marketing Channels: Evidence From West Bengal," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 55(187), pages 87-108, October –.
  • Handle: RePEc:beo:journl:v:55:y:2010:i:187:p:87-108
    as

    Download full text from publisher

    File URL: http://www.ekof.bg.ac.rs/wp-content/uploads/2014/06/187-1-4.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pawar, Jagannathrao R. & Sawant, Sitaram K., 1979. "Comparative Efficiency of Alternative Milk Marketing Agencies in Western Maharashtra," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 34(4), October.
    2. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    3. Rangasamy, N. & Dhaka, J.P., 2008. "Marketing Efficiency of Dairy Products for Co-operative and Private Dairy Plants in Tamil Nadu - A Comparative Analysis," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 21(2).
    4. Singh, Virender & Rai, K.N., 1998. "Economics of Production and Marketing of Buffalo Milk in Haryana," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 53(1), March.
    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. Simpson, N.C. & Tacheva, Zhasmina & Kao, Ta-Wei, 2023. "Semi-directedness: New network concepts for supply chain research," International Journal of Production Economics, Elsevier, vol. 256(C).
    2. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    3. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, April.
    4. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    5. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    6. Ruiqing Yuan & Xiangyang Xu & Yanli Wang & Jiayi Lu & Ying Long, 2024. "Evaluating Carbon-Emission Efficiency in China’s Construction Industry: An SBM-Model Analysis of Interprovincial Building Heating," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
    7. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    8. Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & de Pinho Matos, Giordano Bruno Braz, 2015. "Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 47-60.
    9. Gilligan, Daniel O., 1998. "Farm Size, Productivity, And Economic Efficiency: Accounting For Differences In Efficiency Of Farms By Size In Honduras," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20918, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Ahmad, Usman, 2011. "Financial Reforms and Banking Efficiency: Case of Pakistan," MPRA Paper 34220, University Library of Munich, Germany.
    11. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    12. Juan Aparicio & Jesus T. Pastor & Jose L. Sainz-Pardo & Fernando Vidal, 2020. "Estimating and decomposing overall inefficiency by determining the least distance to the strongly efficient frontier in data envelopment analysis," Operational Research, Springer, vol. 20(2), pages 747-770, June.
    13. Büschken, Joachim, 2009. "When does data envelopment analysis outperform a naïve efficiency measurement model?," European Journal of Operational Research, Elsevier, vol. 192(2), pages 647-657, January.
    14. Barros, Carlos Pestana & Williams, Jonathan, 2013. "The random parameters stochastic frontier cost function and the effectiveness of public policy: Evidence from bank restructuring in Mexico," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 98-108.
    15. Watkins, K. Bradley & Hristovska, Tatjana & Mazzanti, Ralph & Wilson, Charles E. Jr & Schmidt, Lance, 2014. "Measurement of Technical, Allocative, Economic, and Scale Efficiency of Rice Production in Arkansas Using Data Envelopment Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 46(1), pages 1-18, February.
    16. Jahangoshai Rezaee, Mustafa & Jozmaleki, Mehrdad & Valipour, Mahsa, 2018. "Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 78-93.
    17. Suhyeon Han & Shinyoung Park & Sejin An & Wonjun Choi & Mina Lee, 2023. "Research on Analyzing the Efficiency of R&D Projects for Climate Change Response Using DEA–Malmquist," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    18. Chenini Hajer & Jarboui Anis, 2018. "Analysis of the Impact of Governance on Bank Performance: Case of Commercial Tunisian Banks," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 871-895, September.
    19. Chai, Naijie & Zhou, Wenliang & Hu, Xinlei, 2022. "Safety evaluation of urban rail transit operation considering uncertainty and risk preference: A case study in China," Transport Policy, Elsevier, vol. 125(C), pages 267-288.
    20. Yande Gong & Joe Zhu & Ya Chen & Wade D. Cook, 2018. "DEA as a tool for auditing: application to Chinese manufacturing industry with parallel network structures," Annals of Operations Research, Springer, vol. 263(1), pages 247-269, April.

    More about this item

    Keywords

    Primary Milk Producers’ Co-operative Society; Milk vendor; Price spread; Marketing cost; Measure of marketing efficiency; profit efficiency;
    All these keywords.

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

    Statistics

    Access and download statistics

    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:beo:journl:v:55:y:2010:i:187:p:87-108. 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: Goran Petrić (email available below). General contact details of provider: https://edirc.repec.org/data/efbeoyu.html .

    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.