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Cost Efficiency Of Agroindustrial Companies In Vojvodina: Dea Approach

Author

Listed:
  • Vunjak Nenad

    (University of Novi Sad, Faculty of Economics in Subotica, Republic of Serbia)

  • Davidovic Milivoje

    (University of Novi Sad, Faculty of Economics in Subotica, Republic of Serbia)

Abstract

The aim of this study is to assess the cost efficiency of 25 agro-industrial companies in Vojvodina. The analysis covers the period from 2010 to 2012, and the efficiency of the companies is estimated using the non-parametric DEA techniques. Data Envelopment Analysis (DEA) is a linear programming technique that estimates technical efficiency using the input-output model. This paper will apply an input oriented model with (a) constant returns to scale (CCR model), (b) variable returns to scale (BCC model). Results of CCR and BCC models indicate that the agro-industrial sector in Vojvodina increased the average efficiency score (from 80.45% to 86.97% (CCR) and from 89.37% to 90.74% (BCC)). Also, researc indicates that the introduction of bankruptcy proceedings coincided with improving the efficiency scores and ranking of some companies.

Suggested Citation

  • Vunjak Nenad & Davidovic Milivoje, 2014. "Cost Efficiency Of Agroindustrial Companies In Vojvodina: Dea Approach," Interdisciplinary Management Research, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 10, pages 369-376.
    • Handle: RePEc:osi:journl:v:10:y:2014:p:369-376
    as

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    References listed on IDEAS

    as
    1. Holmgren, Johan, 2013. "The efficiency of public transport operations – An evaluation using stochastic frontier analysis," Research in Transportation Economics, Elsevier, vol. 39(1), pages 50-57.
    2. Sara G.Castellanos & Jesus G. Garza-Garcia, 2013. "Competition and Efficiency in the Mexican Banking Sector," Working Papers 1329, BBVA Bank, Economic Research Department.
    3. Andries, Alin Marius & Cocris, Vasile, 2010. "A Comparative Analysis of the Efficiency of Romanian Banks," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 54-75, December.
    4. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2006. "Cost Efficiency in Regional Bus Companies: An Application of Alternative Stochastic Frontier Models," Journal of Transport Economics and Policy, University of Bath, vol. 40(1), pages 95-118, January.
    5. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    cost efficiency; agro-industrial companies; DEA approach; BCC model; CCR model;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure

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