IDEAS home Printed from https://ideas.repec.org/a/bap/journl/130204.html
   My bibliography  Save this article

Efficiency Variation of Manufacturing Firms: A Case Study of Seafood Processing Firms in Bangladesh

Author

Listed:
  • Md. Shakil Ahmed

    (Research and Evaluation Division, BRAC, Bangladesh)

  • M. Daud Ahmed

    (Faculty of Business, Manukau Institute of Technology, New Zealand)

Abstract

Manufacturing firms in developing countries experience difficulties to deploy total capacity and realize the full potential. This research uses four years? primary data collected from the seafood industry in Bangladesh and analyzes that using stochastic frontier approach and presents an estimation model of the technical efficiency of the seafood processing firms in Bangladesh. It reveals that the industry runs on an average of 80% technical efficiency and has the potentials to increase productivity efficiency. The research also finds that the firms? age and size are the main sources of inefficiency. Smaller and newer firms are comparatively efficient than the larger and older ones. In order to improve production efficiency, large firms need to devise strategies for regular modernization through technological adaptation and modularization of the production units.

Suggested Citation

  • Md. Shakil Ahmed & M. Daud Ahmed, 2013. "Efficiency Variation of Manufacturing Firms: A Case Study of Seafood Processing Firms in Bangladesh," Review of Economics & Finance, Better Advances Press, Canada, vol. 3, pages 45-56, May.
    • Handle: RePEc:bap:journl:130204
    as

    Download full text from publisher

    File URL: http://www.bapress.ca/ref/v3-2/1923-7529-2013-02-45-12.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tom Kompas & Tuong Nhu Che & R. Quentin Grafton, 2004. "Technical efficiency effects of input controls: evidence from Australia's banana prawn fishery," Applied Economics, Taylor & Francis Journals, vol. 36(15), pages 1631-1641.
    2. Mercedes Gumbau-Albert & Joaquin Maudos, 2002. "The determinants of efficiency: the case of the Spanish industry," Applied Economics, Taylor & Francis Journals, vol. 34(15), pages 1941-1948.
    3. Derek Jones & Panu Kalmi & Mikko Mäkinen, 2010. "The productivity effects of stock option schemes: evidence from Finnish panel data," Journal of Productivity Analysis, Springer, vol. 33(1), pages 67-80, February.
    4. Ray,Subhash C., 2012. "Data Envelopment Analysis," Cambridge Books, Cambridge University Press, number 9781107405264, October.
    5. Wadud, Md. Abdul., 2003. "Technical, Allocative, and economic efficiency of farms in Bangladesh: a stochastic frontier and DEA approach," Journal of Developing Areas, Tennessee State University, College of Business, vol. 37(1), pages 109-126, September.
    6. Víctor Moreira & Boris Bravo-Ureta, 2010. "Technical efficiency and metatechnology ratios for dairy farms in three southern cone countries: a stochastic meta-frontier model," Journal of Productivity Analysis, Springer, vol. 33(1), pages 33-45, February.
    7. Li, Hongbin & Rozelle, Scott, 2000. "Saving or stripping rural industry: an analysis of privatization and efficiency in China," Agricultural Economics, Blackwell, vol. 23(3), pages 241-252, September.
    8. Anup Kumar Bhandari & Pradip Maiti, 2007. "Efficiency of Indian Manufacturing Firms: Textile Industry as a Case Study," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 6(1), pages 71-88, April.
    9. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    10. Ruhul A. Salim, 2006. "Measuring Productive Efficiency Incorporating Firms¡¯ Heterogeneity: An Empirical Analysis," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 31(1), pages 135-147, June.
    11. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    12. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    13. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    14. Bakht, Zaid & Salimullah, Md. & Yamagata, Tatsufumi & Yunus, Mohammad, 2008. "Competitiveness of the knitwear industry in Bangladesh : a study of industrial development amid global competition," IDE Discussion Papers 169, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    15. Caves, Richard E., 1989. "International differences in industrial organization," Handbook of Industrial Organization, in: R. Schmalensee & R. Willig (ed.), Handbook of Industrial Organization, edition 1, volume 2, chapter 21, pages 1225-1250, Elsevier.
    16. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    17. Chavas, Jean-Paul & Aliber, Michael, 1993. "An Analysis Of Economic Efficiency In Agriculture: A Nonparametric Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(1), pages 1-16, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yordanos Gebremeskel & Bupe Simuchimba & Chonzi Mulenga, 2019. "Skills Gap, Innovation, and Firms Performance in Zambia," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(8), pages 129-129, August.
    2. Mohammad Kamal Hossain & Md Abdus Salam & Afsana Nahid, 2022. "Measuring the technical efficiency of the listed IT companies: Evidence from Bangladesh," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 11(6), pages 74-85, September.
    3. Anastasia R. Njiku & Ganka D. Nyamsogoro, 2018. "Determinants of Technical Efficiency of Small Scale Sunflower Oil Processing Firms in Tanzania: One Stage Stochastic Frontier Approach," Asian Journal of Economics and Empirical Research, Asian Online Journal Publishing Group, vol. 5(1), pages 79-86.

    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. Roy, Manish & Mazumder, Ritwik, 2016. "Technical Efficiency of Fish Catch in Traditional Fishing: A Study in Southern Assam," Journal of Regional Development and Planning, Rajarshi Majumder, vol. 5(1), pages 55-68.
    2. Tim J. Coelli, 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 219-245, December.
    3. Larson, Donald F. & Plessmann, Frank, 2009. "Do farmers choose to be inefficient? Evidence from Bicol," Journal of Development Economics, Elsevier, vol. 90(1), pages 24-32, September.
    4. Saldias, Rodrigo & von Cramon-Taubadel, Stephan, 2012. "Access to credit and the determinants of technical inefficiency among specialized small farmers in Chile," DARE Discussion Papers 1211, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    5. repec:aer:wpaper:324 is not listed on IDEAS
    6. Tom Kompas & Tuong Nhu Che & R. Quentin Grafton, 2004. "Technical efficiency effects of input controls: evidence from Australia's banana prawn fishery," Applied Economics, Taylor & Francis Journals, vol. 36(15), pages 1631-1641.
    7. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    8. Roberto Furesi & Fabio Madau & Pietro Pulina, 2013. "Technical efficiency in the sheep dairy industry: an application on the Sardinian (Italy) sector," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 1(1), pages 1-11, December.
    9. Subal Kumbhakar & Efthymios Tsionas, 2008. "Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks," Empirical Economics, Springer, vol. 34(3), pages 585-602, June.
    10. Christopher F. Parmeter & Hung-Jen Wang & Subal C. Kumbhakar, 2017. "Nonparametric estimation of the determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 47(3), pages 205-221, June.
    11. Maruyama, Eduardo & Schollard, Phoebe, 2021. "Geographic prioritization of agricultural investments: Prioritization of agricultural and nutrition investments," 2021 Conference, August 17-31, 2021, Virtual 315292, International Association of Agricultural Economists.
    12. Henderson, Heath & Follett, Lendie, 2022. "Targeting social safety net programs on human capabilities," World Development, Elsevier, vol. 151(C).
    13. Tauer, Loren W. & Mishra, Ashok K., 2006. "Can the small dairy farm remain competitive in US agriculture?," Food Policy, Elsevier, vol. 31(5), pages 458-468, October.
    14. Deng, Yaguo, 2024. "A Bayesian semi-parametric approach to stochastic frontier models with inefficiency heterogeneity," DES - Working Papers. Statistics and Econometrics. WS 43837, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Zoltan Bakucs & Imre Fertő & József Fogarasi & Laure Latruffe & Yann Desjeux & Eduard Matveev & Sonia Marongiu & Mark Dolman & Rafat Soboh, 2011. "EU farms’ technical efficiency and productivity change in 1990 – 2006 [Efficacité technique et changement de productivité des exploitations agricoles européennes 1990-2006]," Post-Print hal-02808334, HAL.
    16. Thi Bich Tran & R. Quentin Grafton & Tom Kompas, 2008. "Firm Efficiency in a Transitional Economy: Evidence from Vietnam," Asian Economic Journal, East Asian Economic Association, vol. 22(1), pages 47-66, March.
    17. Madau, Fabio A., 2005. "Technical Efficiency in Organic Farming: An Application on Italian Cereal Farms Using a Parametric Approach," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24545, European Association of Agricultural Economists.
    18. Lajos Zoltan Bakucs & Laure Latruffe & Imre Ferto & Jozsef Fogarasi, 2006. "Technical efficiency of Hungarian farms before and after accession," Post-Print hal-02285626, HAL.
    19. Vangelis Tzouvelekas & Konstantinos Giannakas & Peter Midmore & Konstantinos Mattas, 1997. "Technical efficiency measures for olive-growing farms in Crete, Greece," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 3(2), pages 154-169, May.
    20. Alejandro Esteller-Moré, 2005. "Is There a Connection Between the Tax Administration and the Political Power?," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 12(5), pages 639-663, September.
    21. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.

    More about this item

    Keywords

    Stochastic production function; Technical efficiency; Seafood processing firms; Production efficiency factors;
    All these keywords.

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L66 - Industrial Organization - - Industry Studies: Manufacturing - - - Food; Beverages; Cosmetics; Tobacco

    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:bap:journl:130204. 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: Carlson (email available below). General contact details of provider: http://www.bapress.ca .

    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.