Agric. Econ. - Czech, 2026, 72(9):540-558 | DOI: 10.17221/359/2025-AGRICECON

Measuring the efficiency of agropastoral systems in Inner Mongolia: Parallel bounded adjusted measure with shared inputs and outputsOriginal Paper

Chunhua Chen ORCID...1, Wenjing Song ORCID...2, Ruizhi Wang ORCID...3, Chongyu Ma ORCID...4
1 College of Economics and Management, Inner Mongolia Agricultural University, Hohhot, P.R. China
2 Shaanxi Yanchang Petroleum (Group), Xian, P.R. China
3 Transportation Institute, Inner Mongolia University, Hohhot, P.R. China
4 Transportation Institute, Southeast University, Nanjing, P.R. China

Inner Mongolia operates using integrated agropastoral systems comprising crop and livestock production subsystems. To evaluate the efficiency of these interconnected subsystems, we develop an innovative parallel-bounded adjusted measure (BAM) model with shared inputs and outputs. Unlike conventional data envelopment analysis (DEA) models, this approach explicitly accounts for parallel structures with shared inputs and outputs, allowing for a more precise and nuanced assessment of efficiency. Our results are as follows: (i) regional efficiency disparities: Hohhot City, Ordos City, and Wuhai City are efficient, whereas Ulanqab City performs the worst; (ii) subsystem performance: crop production subsystems generally outperform livestock production subsystems; (iii) inefficiencies: we observe significant input slacks in cultivated land area, total agricultural machinery power, and initial livestock numbers, whereas the disposable income of rural residents requires significant improvement.

Keywords: griculture; crop; data envelopment analysis; livestock; shared resources

Received: August 31, 2025; Revised: April 25, 2026; Accepted: May 4, 2026; Prepublished online: September 7, 2026; Published: September 30, 2026  Show citation

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Chen C, Song W, Wang R, Ma C. Measuring the efficiency of agropastoral systems in Inner Mongolia: Parallel bounded adjusted measure with shared inputs and outputs. Agricultural Economics. 2026;72(9):540-558. doi: 10.17221/359/2025-AGRICECON.
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    References

    1. Arya A., Singh S. (2021): Development of two-stage parallel-series system with fuzzy data: A fuzzy DEA approach. Soft Computing, 25: 3225-3245. Go to original source...
    2. Beasley J.E. (1995): Determining teaching and research efficiencies. Journal of the Operational Research Society, 46: 441-452. Go to original source...
    3. Bian Y., Hu M., Xu H. (2015): Measuring efficiencies of parallel systems with shared inputs/outputs using data envelopment analysis. Kybernetes, 44: 336-352. Go to original source...
    4. Chen P.C., Hsu S.H., Chang C.C., Yu M.M. (2013): Efficiency measurements in multi-activity data envelopment analysis with shared inputs: An application to farmers' cooperatives in Taiwan. China Agricultural Economic Review, 5: 24-42. Go to original source...
    5. Cheng X.J., Bian J.X., He D.M., Tang D.C. (2025): An analysis of agricultural production efficiency of Yellow River Basin based on a three-stage DEA Malmquist model. Humanities and Social Sciences Communications, 12: 1343. Go to original source...
    6. Cook W.D., Hababou M., Tuenter H.J.H. (2000): Multicomponent efficiency measurement and shared inputs in data envelopment analysis: An application to sales and service performance in bank branches. Journal of Productivity Analysis, 14: 209-224. Go to original source...
    7. Cooper W.W., Pastor J.T., Borras F., Aparicio J., Pastor D. (2011): BAM: A bounded adjusted measure of efficiency for use with bounded additive models. Journal of Productivity Analysis, 35: 85-94. Go to original source...
    8. Fang L. (2016). Agricultural production efficiency in China's provincial regions based on DEA method. Agro Food Industry Hi-Tech, 27: 119-124.
    9. Hajihassaniasl S. (2022): Technical efficiency determinants of OECD countries' agricultural production: A stochastic frontier analysis approach. Scientific Papers Series Management, Economic Engineering in Agriculture and Rural Development, 22: 279-288.
    10. Han G., Yang H., Xie H. (2024): Research on the efficiency and spatiotemporal evolution characteristics of agricultural green development in central cities of the Yangtze River Delta. Frontiers in Environmental Science, 12: 1502824. Go to original source...
    11. He X.Y., Peng W.Y., Li R.F. (2019): Evaluation of modern agricultural development efficiency based on DEA: Take Dengkou County of Inner Mongolia as the sample. Research of Soil and Water Conservation, 26: 374-380. (in Chinese)
    12. Kao C. (2009): Efficiency measurement for parallel production systems. European Journal of Operational Research, 196: 1107-1112. Go to original source...
    13. Kao C. (2012): Efficiency decomposition for parallel production systems. Journal of the Operational Research Society, 63: 64-71. Go to original source...
    14. Kao C. (2014): Network data envelopment analysis: A review. European Journal of Operational Research, 239: 1-16. Go to original source...
    15. Khan D., Nouman M., Ullah A. (2023): Assessing the impact of technological innovation on technically derived energy efficiency: A multivariate co-integration analysis of the agricultural sector in South Asia. Environment, Development and Sustainability, 25: 3723-3745. Go to original source...
    16. Kuang B., Lu X., Zhou M., Chen D. (2020): Provincial cultivated land use efficiency in China: Empirical analysis based on the SBM-DEA model with carbon emissions considered. Technological Forecasting and Social Change, 151: 119874. Go to original source...
    17. Lei X., Li L., Zhang X., Dai Q., Fu Y. (2019): A novel ratio-based parallel DEA approach for evaluating the energy and environmental performance of Chinese transportation sectors. Journal of Systems Science and Systems Engineering, 28: 621-635. Go to original source...
    18. Li Y., Huang X.C., Cui Q. (2022): Exploring the environmental efficiency of airlines through a parallel RAM approach. Energy Efficiency, 15: 45. Go to original source... Go to PubMed...
    19. Liu X., Li Y. (2024): Evaluation of county agricultural eco-efficiency in Chongqing and analysis of its spatiotemporal differentiation under the dual carbon target. Polish Journal of Environmental Studies, 33: 2177-2191. Go to original source...
    20. Low G., Dalhaus T., Meuwissen M.P.M. (2023): Mixed farming and agroforestry systems: A systematic review on value chain implications. Agricultural Systems, 206: 103606. Go to original source...
    21. Lozano S. (2015): A joint-inputs Network DEA approach to production and pollution-generating technologies. Expert Systems with Applications, 42: 7960-7968. Go to original source...
    22. Ma J.F. (2015): A two-stage DEA model considering shared inputs and free intermediate measures. Expert Systems with Applications, 42: 4339-4347. Go to original source...
    23. Molinero C.M. (1996): On the joint determination of efficiencies in a data envelopment analysis context. Journal of the Operational Research Society, 47: 1273-1279. Go to original source...
    24. Moulay A.H., Guellil M.S., Mokhtari F., Tsabet A. (2024): The effect of subsidies on technical efficiency of Algerian agricultural sector: Using stochastic frontier model (SFA). Discover Sustainability, 5: 98. Go to original source...
    25. National Bureau of Statistics of China (2025): China Statistical Yearbook 2025. [Statistical dataset]. Beijing, China Statistics Press.
    26. Phung M.T., Cheng C.P., Guo C., Kao C.Y. (2020): Mixed network DEA with shared resources: A case of measuring performance for banking industry. Operations Research Perspectives, 7: 100173. Go to original source...
    27. Qimuge G., Tuya W., Qinchaoketu S., He B. (2023): Construction and practice of livelihood efficiency index system for herders in typical steppe area of Inner Mongolia based on super-efficiency slacks-based measure model. Sustainability, 15: 14005. Go to original source...
    28. Rybaczewska-Błażejowska M., Gierulski W. (2018): Eco-efficiency evaluation of agricultural production in the EU-28. Sustainability, 10: 4544. Go to original source...
    29. Song D., Chen F., Ouyang X. (2024): The impact of changes in rural family structure on agricultural productivity and efficiency: Evidence from rice farmers in China. Sustainability, 16: 3892. Go to original source...
    30. Stefaniec A., Hosseini K., Xie J., Li Y. (2020): Sustainability assessment of inland transportation in China: A triple bottom line-based network DEA approach. Transportation Research Part D: Transport and Environment, 80: 102258. Go to original source...
    31. Thomassen M.A., van Calker K.J., Smits M.C.J., Iepema G.L., de Boer I.J.M. (2008): Life cycle assessment of conventional and organic milk production in the Netherlands. Agricultural Systems, 96: 95-107. Go to original source...
    32. Thornton P., Herrero M., Nelson G., Mayberry D. (2024): Resilient livelihoods in Africa's pastoral-agropastoral transition zones will increasingly depend on heat stress adaptation and systemic change. Nature Food, 5: 976-981. Go to original source... Go to PubMed...
    33. Tsai P.F., Molinero C.M. (2002): A variable returns to scale data envelopment analysis model for the joint determination of efficiencies with an example of the UK health service. European Journal of Operational Research, 141: 21-38. Go to original source...
    34. Wang G.F., Zhao M.Q., Zhao B.H., Liu X., Wang Y. (2025): Reshaping agriculture eco-efficiency in China: From greenhouse gas perspective. Ecological Indicators, 172: 113268. Go to original source...
    35. Yang S., Wang H., Tong J., Ma J., Zhang F., Wu S. (2020): Technical efficiency of China's agriculture and output elasticity of factors based on water resources utilization. Water, 12: 2691. Go to original source...
    36. Zhang L., Du X., Chiu Y.H., Pang Q., WangX., Yu Q. (2022): Measuring industrial operational efficiency and factor analysis: A dynamic series-parallel recycling DEA model. Science of the Total Environment, 851: 158084. Go to original source... Go to PubMed...
    37. Zhang J.N., Hou G.Q., Xing L. (2024): Influence of the utilization level of agricultural machinery socialized service on farmers' production efficiency: A case study of corn growers in Inner Mongolia. Journal of Chinese Agricultural Mechanization, 45: 320-329. (in Chinese)
    38. Zhang H., Deng W., Zhang S.Y., Wang Z.Y. (2026): Multiscale geospatial transitions and sustainable strategies for mountainous urban agglomerations: From the perspective of social-ecological systems. Cities, 169: 106560. Go to original source...
    39. Zhao Y., Jiang Q., Wang Z. (2019): The system evaluation of grain production efficiency and analysis of driving factors in Heilongjiang province. Water, 11: 1073. Go to original source...
    40. Zhong F.L., Liu Y.S., Ma Y.L., Li Y.L., He M. (2025): The government's impact on the transformation of rural livelihoods in agropastoral regions: A quantitative analysis of farmers' perceptions of public services in Inner Mongolia, China. Land Use Policy, 157: 107642. Go to original source...

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