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Efficiency and Productivity Changes in the Indian Food Processing Industry: Determinants and Policy Implications

Author

Listed:
  • Ali, Jabir
  • Singh, Surendra P.
  • Ekanem, Enefiok P.

Abstract

This paper analyses efficiency and productivity changes in 12 broad segments of food manufacturing industries during pre and post liberalisation periods, covering a period of two decades, from 1980-1981 to 2001-2002. The nonparametric Data Envelopment Analysis (DEA) approach is used to compute the Malmquist Total Factor Productivity (TFP) change, which has been further decomposed into efficiency and technical change. This paper also evaluates the performance of major inputs used in the food processing industry and identifies the causes of inefficiency across various segments. Based on the findings, the paper gives suggestions that can be used by policy makers and food processors in making decisions regarding various technical and managerial aspects to improve productivity and efficiency.

Suggested Citation

  • Ali, Jabir & Singh, Surendra P. & Ekanem, Enefiok P., 2009. "Efficiency and Productivity Changes in the Indian Food Processing Industry: Determinants and Policy Implications," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 12(1), pages 1-24, February.
    • Handle: RePEc:ags:ifaamr:53745
    DOI: 10.22004/ag.econ.53745
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    Citations

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    Cited by:

    1. Kapelko, Magdalena & Oude Lansink, Alfons, 2017. "Dynamic multi-directional inefficiency analysis of European dairy manufacturing firms," European Journal of Operational Research, Elsevier, vol. 257(1), pages 338-344.
    2. Margareta Gardijan & Zrinka Lukač, 2018. "Measuring the relative efficiency of the food and drink industry in the chosen EU countries using the data envelopment analysis with missing data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 695-713, September.
    3. Magdalena Kapelko, 2017. "Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis," Agribusiness, John Wiley & Sons, Ltd., vol. 33(4), pages 505-521, September.
    4. Majiwa, E. & Mugodo, C., 2018. "Technical efficiency and technology gap ratios among rice farmers in Kenya," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277209, International Association of Agricultural Economists.
    5. Eucabeth Majiwa & Boon L. Lee & Clevo Wilson & Hidemichi Fujii & Shunsuke Managi, 2018. "A network data envelopment analysis (NDEA) model of post-harvest handling: the case of Kenya’s rice processing industry," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 631-648, June.
    6. Reardon, Thomas, 2011. "The global rise and impact of supermarkets: an international perspective," 2011: The Supermarket Revolution in Food: Good, Bad or Ugly for the World's Farmers, Consumers and Retailers?, 14-16 August 2011 125312, Crawford Fund.
    7. Tiwari, Rajnish, 2017. "Propositions for a high-quality, affordable and sustainable Food Basket : scope of cooperation between India & Germany in areas relating to food processing industry," EconStor Research Reports 157662, ZBW - Leibniz Information Centre for Economics.
    8. Magdalena Kapelko, 2019. "Measuring productivity change accounting for adjustment costs: evidence from the food industry in the European Union," Annals of Operations Research, Springer, vol. 278(1), pages 215-234, July.
    9. Gardijan Kedžo, Margareta & Lukač, Zrinka, 2021. "The financial efficiency of small food and drink producers across selected European Union countries using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 291(2), pages 586-600.
    10. Magdalena Kapelko & Alfons Oude Lansink & Spiro E. Stefanou, 2017. "Input-Specific Dynamic Productivity Change: Measurement and Application to European Dairy Manufacturing Firms," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(2), pages 579-599, June.
    11. Magdalena Kapelko & Alfons Oude Lansink, 2018. "Managerial and program inefficiency for European meat manufacturing firms: A dynamic multidirectional inefficiency analysis approach," Journal of Productivity Analysis, Springer, vol. 49(1), pages 25-36, February.
    12. Magdalena Kapelko & Alfons Oude Lansink, 2020. "Dynamic Cost Inefficiency of the European Union Meat Processing Firms," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 760-777, September.
    13. Chieh-Wen Chang & Kun-Shan Wu & Bao-Guang Chang & Kuo-Ren Lou, 2019. "Measuring Technical Efficiency and Returns to Scale in Taiwan’s Baking Industry―A Case Study of the 85 °C Company," Sustainability, MDPI, vol. 11(5), pages 1-14, February.
    14. Chieh-Wen Chang & Kun-Shan Wu & Bao-Guang Chang, 2019. "Productivity Change and Decomposition in Taiwan Bakery Enterprise―Evidence from 85 °C Company," Sustainability, MDPI, vol. 11(24), pages 1-13, December.
    15. Nithyashree, M L, 2021. "The role of the macro environment and firm-specific characteristics in improving the resource use efficiency of the Indian food processing industry," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 34(Conferenc), October.

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