IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i10p1604-d932740.html
   My bibliography  Save this article

The Technical Efficiency of Beef Calf Production Systems: Evidence from a Survey in Hebei, China

Author

Listed:
  • Yongjie Xue

    (School of Economics, Shandong Women’s University, Jinan 250300, China)

  • Jinling Yan

    (College of Economics and Management, Hebei Agricultural University, Baoding 071001, China)

  • Yongfu Cui

    (College of Economics and Management, Hebei Agricultural University, Baoding 071001, China)

  • Huifeng Zhao

    (College of Economics and Management, Hebei Agricultural University, Baoding 071001, China)

  • Ya’nan Zhang

    (College of Economics and Management, Hebei Agricultural University, Baoding 071001, China)

  • Changhai Ma

    (College of Economics and Management, Hebei Agricultural University, Baoding 071001, China)

  • Haijing Zheng

    (Research Faculty of Agriculture, Hokkaido University, Sapporo 060-0808, Japan)

Abstract

Beef calf production is a source of sustainable development for the beef cattle industry. However, no comparative studies have reported on the technical efficiency of different beef calf production systems and their influencing factors. Based on data from 218 Chinese farmers and 12 governments, in the present study, we constructed data envelopment analysis (DEA) models and conducted a comparative analysis of the technical efficiency of the main three beef calf production systems: the Simmental calf intensive production system (CIPS), Simmental calf semi-intensive production system (SCIPS) and Holstein bull calf intensive production system (BCIPS). Using Tobit models, we analyzed the effects of various factors. The results show that: (1) The technical efficiency of the production system of Simmental calf is higher than that of Holstein bull calf, and the efficiency of SCIPS is higher than that of CIPS. The technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of different systems are significantly different. (2) Policy on the environment positively affected ( p < 0.01) the TE, TPE and SE of CIPS, but negatively affected the PTE of SCIPS. Therefore, appropriate environmental regulations have a positive effect on production efficiency, which means that measures should be taken according to the reality and characteristics of the production system, and policies applicable to other systems or regions may not be applicable in a given case. (3) The management level and technology training had positive effects on the TE, TPE and SE of the three systems, while the number of years of production had a negative or no significant effect. Producers are not the “perfectly rational economic man”, and the more knowledge they have, the more productive they will be. However, the “knowledge” referred to here is that which is adapted to production, not that which is traditional. The knowledge possessed by the producer should be updated continuously with the changes over time and the development of the industry, while outdated information is not considered as “knowledge” here. Therefore, to achieve sustainability, the government should fully consider the characteristics of the local breeding mode and, more importantly, the expected effects of policies to be implemented.

Suggested Citation

  • Yongjie Xue & Jinling Yan & Yongfu Cui & Huifeng Zhao & Ya’nan Zhang & Changhai Ma & Haijing Zheng, 2022. "The Technical Efficiency of Beef Calf Production Systems: Evidence from a Survey in Hebei, China," Agriculture, MDPI, vol. 12(10), pages 1-22, October.
  • Handle: RePEc:gam:jagris:v:12:y:2022:i:10:p:1604-:d:932740
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/10/1604/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/12/10/1604/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Otieno, David Jakinda & Hubbard, Lionel J. & Ruto, Eric, 2011. "Technical efficiency and technology gaps in beef cattle production systems in Kenya: A stochastic metafrontier analysis," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108947, Agricultural Economics Society.
    3. Featherstone, Allen M. & Langemeier, Michael R. & Ismet, Mohammad, 1997. "A Nonparametric Analysis Of Efficiency For A Sample Of Kansas Beef Cow Farms," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 29(1), pages 1-10, July.
    4. Tamer Işgın & Remziye Özel & Abdulbaki Bilgiç & Wojciech J. Florkowski & Mehmet Reşit Sevinç, 2020. "DEA Performance Measurements in Cotton Production of Harran Plain, Turkey: A Single and Double Bootstrap Truncated Regression Approaches," Agriculture, MDPI, vol. 10(4), pages 1-17, April.
    5. Wubeneh, Nega & Ehui, Simeon K., 2006. "Technical Efficiency of Smallholder Dairy Farmers in the Central Ethiopian Highlands," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25640, International Association of Agricultural Economists.
    6. Rakipova, Anna N. & Gillespie, Jeffrey M. & Franke, Donald E., 2003. "Determinants of Technical Efficiency in Louisiana Beef Cattle Production," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2003, pages 1-9.
    7. Linda Argote & Ella Miron-Spektor, 2011. "Organizational Learning: From Experience to Knowledge," Organization Science, INFORMS, vol. 22(5), pages 1123-1137, October.
    8. María Pérez Urdiales & Alfons Oude Lansink & Alan Wall, 2016. "Eco-efficiency Among Dairy Farmers: The Importance of Socio-economic Characteristics and Farmer Attitudes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(4), pages 559-574, August.
    9. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    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. Wang, Tong & Park, Seong C. & Bevers, Stan & Teague, Richard & Cho, Jaesung, 2013. "Factors Affecting Cow-Calf Herd Performance and Greenhouse Gas Emissions," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(3), pages 1-22.
    2. Otieno, David Jakinda & Hubbard, Lionel J. & Ruto, Eric, 2011. "Technical efficiency and technology gaps in beef cattle production systems in Kenya: A stochastic metafrontier analysis," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108947, Agricultural Economics Society.
    3. Nwigwe, Cecilia & Okoruwa, Victor & Obi-Egbedi, Oghenerueme, 2015. "Efficiency differentials and technological gaps in beef cattle production systems in Nigeria," 2015 Conference, August 9-14, 2015, Milan, Italy 229377, International Association of Agricultural Economists.
    4. 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.
    5. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    6. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    7. Artur Wyszyński, 2017. "Sytuacja finansowa klubów Ekstraklasy w ujęciu metody DEA," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 69-99.
    8. Oleg Badunenko & Harald Tauchmann, 2019. "Simar and Wilson two-stage efficiency analysis for Stata," Stata Journal, StataCorp LP, vol. 19(4), pages 950-988, December.
    9. Mario Fortin & André Leclerc, 2011. "L’Efficience Des Cooperatives De Services Financiers: Une Analyse De La Contribution Du Milieu," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 82(1), pages 45-62, March.
    10. Ningyi Liu & Yongyu Wang, 2022. "Urban Agglomeration Ecological Welfare Performance and Spatial Convergence Research in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-18, November.
    11. Vicente J. Bolós & Rafael Benítez & Vicente Coll-Serrano, 2023. "Continuous models combining slacks-based measures of efficiency and super-efficiency," 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. 31(2), pages 363-391, June.
    12. Liu, Fuh-Hwa Franklin & Wang, Peng-hsiang, 2008. "DEA Malmquist productivity measure: Taiwanese semiconductor companies," International Journal of Production Economics, Elsevier, vol. 112(1), pages 367-379, March.
    13. Yung-ho Chiu & Chin-wei Huang & Chung-te Ting, 2012. "A non-radial measure of different systems for Taiwanese tourist hotels’ efficiency assessment," 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. 20(1), pages 45-63, March.
    14. Yan Zhang & Zihan Xin & Guoya Gan, 2024. "Evaluating the Sustainable Development Performance of China’s International Commercial Ports Based on Environmental, Social and Governance Elements," Sustainability, MDPI, vol. 16(10), pages 1-16, May.
    15. Zhen Shi & Huinan Huang & Yingju Wu & Yung-Ho Chiu & Shijiong Qin, 2020. "Climate Change Impacts on Agricultural Production and Crop Disaster Area in China," IJERPH, MDPI, vol. 17(13), pages 1-23, July.
    16. Tran, Trung Hieu & Mao, Yong & Nathanail, Paul & Siebers, Peer-Olaf & Robinson, Darren, 2019. "Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis," Omega, Elsevier, vol. 85(C), pages 156-165.
    17. Wang, Chia-Nan & Nguyen, Xuan-Tho & Le, Thi-Dao & Hsueh, Ming-Hsien, 2018. "A partner selection approach for strategic alliance in the global aerospace and defense industry," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 190-204.
    18. Hao Su & Shuo Yang, 2022. "Spatio-Temporal Urban Land Green Use Efficiency under Carbon Emission Constraints in the Yellow River Basin, China," IJERPH, MDPI, vol. 19(19), pages 1-28, October.
    19. Soushi Suzuki & Karima Kourtit & Peter Nijkamp, 2017. "The robustness of performance rankings of Asia-Pacific super cities," Asia-Pacific Journal of Regional Science, Springer, vol. 1(1), pages 219-242, April.
    20. Avkiran, Necmi K., 2007. "Stability and integrity tests in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 41(3), pages 224-234, September.

    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:12:y:2022:i:10:p:1604-:d:932740. 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.