IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v22y2020i4d10.1007_s10668-019-00348-x.html
   My bibliography  Save this article

Environmental efficiency of small-scale tea processors in Kenya: an inverse data envelopment analysis (DEA) approach

Author

Listed:
  • Karambu Kiende Gatimbu

    (University of Embu)

  • Maurice Juma Ogada

    (Taita Taveta University)

  • Nancy L. M. Budambula

    (University of Embu)

Abstract

Vision 2030, Kenya’s development blueprint for the period 2008–2030, envisions transforming the country into middle-income status where citizens enjoy a high quality of life. The blueprint has three pillars: economic, political and social. The thread that binds the three pillars is the natural environment, which supplies both renewable and non-renewable resources. Unfortunately, development in the other sectors may easily compromise the conditions of the natural environment and put the supply of clean water, food and fiber in jeopardy. For example, processing of agricultural products may increase gains from agriculture and lead to rapid expansion of the sector. If this is not carefully done, it may be characterized by wastage of resources, cutting down of forests to provide fuel and more land for cultivation, disposal of raw wastes into water bodies and over-exploitation of the soils. Using the example of small-scale tea processors in the country, this study sought to understand the environmental efficiency of the small-scale agro-processors. Small-scale tea processors were chosen because they have been implementing environmental efficiency-enhancing techniques in their production, yet no study had endeavored to test whether their initiatives were yielding positive results. The study adopted the innovative inverse data envelopment analysis approach on panel data to generate environmental efficiency scores, in the first step. In the second step, it analyzed the predictors of environmental efficiency using Tobit regression. Overall, the results showed that small-scale tea processors in Kenya were still environmentally inefficient, recording a mean efficiency index of only 49%, despite previous initiatives to improve efficiency. Thus, the processors could reduce 51% of the environmentally detrimental inputs without compromising output. Environmental inefficiency could be attributed to pursuit for higher profits and higher cost of investible funds. This shows that investment in environmental conservation is expensive and eats into the profits of the processors. Therefore, the small-scale processors may lack the incentives, in the short term, to invest in environment-friendly technologies. This may be compounded by the high cost of finance to be invested in such initiatives. Policy implication is that government should intervene in terms of tax concessions for firms that invest in environmental conservation, subsidies on technologies that guarantee environmental efficiency and access to cheaper funds for purchase and maintenance of environment-friendly technologies.

Suggested Citation

  • Karambu Kiende Gatimbu & Maurice Juma Ogada & Nancy L. M. Budambula, 2020. "Environmental efficiency of small-scale tea processors in Kenya: an inverse data envelopment analysis (DEA) approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(4), pages 3333-3345, April.
  • Handle: RePEc:spr:endesu:v:22:y:2020:i:4:d:10.1007_s10668-019-00348-x
    DOI: 10.1007/s10668-019-00348-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-019-00348-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10668-019-00348-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Basnayake, B.M.J.K. & Gunaratne, L.H.P., 2002. "Estimation of Technical Efficiency and It's Determinants in the Tea Small Holding Sector in the Mid Country Wet Zone of Sri Lanka," Sri Lankan Journal of Agricultural Economics, Sri Lanka Agricultural Economics Association (SAEA), vol. 4, pages 1-15.
    2. Song, Malin & An, Qingxian & Zhang, Wei & Wang, Zeya & Wu, Jie, 2012. "Environmental efficiency evaluation based on data envelopment analysis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4465-4469.
    3. Maity, S., 2017. "Reform Raises Efficiency of Tea Estates in India," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 9(2), June.
    4. Long, Xingle & Zhao, Xicang & Cheng, Faxin, 2015. "The comparison analysis of total factor productivity and eco-efficiency in China's cement manufactures," Energy Policy, Elsevier, vol. 81(C), pages 61-66.
    5. Young-Tae Chang, 2013. "Environmental efficiency of ports: a Data Envelopment Analysis approach," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(5), pages 467-478, September.
    6. Reinhard, Stijn & Knox Lovell, C. A. & Thijssen, Geert J., 2000. "Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA," European Journal of Operational Research, Elsevier, vol. 121(2), pages 287-303, March.
    7. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    8. Yi-Chun Huang & Ying-Jiuan Wong & Min-Li Yang, 2014. "Proactive environmental management and performance by a controlling family," Management Research Review, Emerald Group Publishing Limited, vol. 37(3), pages 210-240, March.
    9. Taulo, J.L. & Sebitosi, A.B., 2016. "Material and energy flow analysis of the Malawian tea industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1337-1350.
    10. Dong Tian & Fengtao Zhao & Weisong Mu & Radoslava Kanianska & Jianying Feng, 2016. "Environmental Efficiency of Chinese Open-Field Grape Production: An Evaluation Using Data Envelopment Analysis and Spatial Autocorrelation," Sustainability, MDPI, vol. 8(12), pages 1-13, November.
    11. 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.
    12. Fang Zhang & Hong Fang & Junjie Wu & Damian Ward, 2016. "Environmental Efficiency Analysis of Listed Cement Enterprises in China," Sustainability, MDPI, vol. 8(5), pages 1-19, May.
    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. Moghaddas, Zohreh & Tosarkani, Babak Mohamadpour & Yousefi, Samuel, 2022. "Resource reallocation for improving sustainable supply chain performance: An inverse data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 252(C).
    2. Mushtaq Taleb & Ruzelan Khalid & Ali Emrouznejad & Razamin Ramli, 2023. "Environmental efficiency under weak disposability: an improved super efficiency data envelopment analysis model with application for assessment of port operations considering NetZero," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6627-6656, July.
    3. Zainab Bibi & Dilawar Khan & Ihtisham ul Haq, 2021. "Technical and environmental efficiency of agriculture sector in South Asia: a stochastic frontier analysis approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(6), pages 9260-9279, June.
    4. Leonidas Sotirios Kyrgiakos & Georgios Kleftodimos & George Vlontzos & Panos M. Pardalos, 2023. "A systematic literature review of data envelopment analysis implementation in agriculture under the prism of sustainability," Operational Research, Springer, vol. 23(1), pages 1-38, March.
    5. Hashem Omrani & Meisam Shamsi & Ali Emrouznejad, 2023. "Evaluating sustainable efficiency of decision-making units considering undesirable outputs: an application to airline using integrated multi-objective DEA-TOPSIS," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 5899-5930, July.
    6. Heidari, Mohammad Davoud & Turner, Ian & Ardestani-Jaafari, Amir & Pelletier, Nathan, 2021. "Operations research for environmental assessment of crop-livestock production systems," Agricultural Systems, Elsevier, vol. 193(C).

    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. Karambu Kiende Gatimbu & Maurice Juma Ogada & Nancy Budambula & Samuel Kariuki, 2018. "Environmental sustainability and financial performance of the small‐scale tea processors in Kenya," Business Strategy and the Environment, Wiley Blackwell, vol. 27(8), pages 1765-1771, December.
    2. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    3. Yigang Wei & Yan Li & Meiyu Wu & Yingbo Li, 2020. "Progressing sustainable development of “the Belt and Road countries”: Estimating environmental efficiency based on the Super‐slack‐based measure model," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 521-539, July.
    4. Chen, Nengcheng & Xu, Lei & Chen, Zeqiang, 2017. "Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models," Energy, Elsevier, vol. 134(C), pages 659-671.
    5. César Salazar & Roberto Cárdenas-Retamal & Marcela Jaime, 2023. "Environmental efficiency in the salmon industry—an exploratory analysis around the 2007 ISA virus outbreak and subsequent regulations in Chile," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8107-8135, August.
    6. Sun, Jiasen & Yuan, Yang & Yang, Rui & Ji, Xiang & Wu, Jie, 2017. "Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis," Transport Policy, Elsevier, vol. 60(C), pages 75-86.
    7. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.
    8. Han-Shen Chen & Bi-Kun Tsai & Gwo-Bao Liou & Chi-Ming Hsieh, 2018. "Efficiency Assessment of Inbound Tourist Service Using Data Envelopment Analysis," Sustainability, MDPI, vol. 10(6), pages 1-14, June.
    9. Ning Zhang & Jong-Dae Kim, 2014. "Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure," Sustainability, MDPI, vol. 6(3), pages 1-13, March.
    10. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    11. Long, Xingle & Wu, Chao & Zhang, Jijian & Zhang, Jing, 2018. "Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: A metafrontier directional slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3962-3971.
    12. Feng, Chao & Wang, Miao, 2018. "Analysis of energy efficiency in China's transportation sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 565-575.
    13. Liu, Xiaohong & Yang, Jiangjiang & Xu, Chengzhen & Li, Xingchen & Zhu, Qingyuan, 2023. "Environmental regulation efficiency analysis by considering regional heterogeneity," Resources Policy, Elsevier, vol. 83(C).
    14. Junfeng Zhang & Jianxu Liu & Jing Li & Yuyan Gao & Chuansong Zhao, 2021. "Green Development Efficiency and Its Influencing Factors in China’s Iron and Steel Industry," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    15. Xionghe Qin & Yanming Sun, 2019. "Cross-Regional Comparative Study on Environmental–Economic Efficiency and Driving Forces behind Efficiency Improvement in China: A Multistage Perspective," IJERPH, MDPI, vol. 16(7), pages 1-21, March.
    16. Nakaishi, Tomoaki & Takayabu, Hirotaka & Eguchi, Shogo, 2021. "Environmental efficiency analysis of China's coal-fired power plants considering heterogeneity in power generation company groups," Energy Economics, Elsevier, vol. 102(C).
    17. Jie Wu & Panpan Xia & Qingyuan Zhu & Junfei Chu, 2019. "Measuring environmental efficiency of thermoelectric power plants: a common equilibrium efficient frontier DEA approach with fixed-sum undesirable output," Annals of Operations Research, Springer, vol. 275(2), pages 731-749, April.
    18. Junfei Chu & Jie Wu & Qingyuan Zhu & Qingxian An & Beibei Xiong, 2019. "Analysis of China’s Regional Eco-efficiency: A DEA Two-stage Network Approach with Equitable Efficiency Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1263-1285, December.
    19. Jiang, Lei & Zhou, Haifeng & He, Shixiong, 2021. "Does energy efficiency increase at the expense of output performance: Evidence from manufacturing firms in Jiangsu province, China," Energy, Elsevier, vol. 220(C).
    20. Xiaowei Song & Yongpei Hao & Xiaodong Zhu, 2015. "Analysis of the Environmental Efficiency of the Chinese Transportation Sector Using an Undesirable Output Slacks-Based Measure Data Envelopment Analysis Model," Sustainability, MDPI, vol. 7(7), pages 1-20, July.

    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:spr:endesu:v:22:y:2020:i:4:d:10.1007_s10668-019-00348-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.