Does Informatization Cause the Relative Substitution Bias of Agricultural Machinery Inputs for Labor Inputs? Evidence from Apple Farmers in China

Congying Zhang

Institute of Western China Economic Research, Southwestern University of Finance and Economics, Chengdu, 611130, China

Jingru Xiang

Institute of Western China Economic Research, Southwestern University of Finance and Economics, Chengdu, 611130, China

Qian Chang

College of Management, Sichuan Agricultural University, Chengdu, 611130, China

DOI: https://doi.org/10.36956/rwae.v4i3.900

Received: 18 July 2023; Received in revised form: 31 August 2023; Accepted: 5 September 2023; Published: 14 September 2023

Copyright © 2023 Congying Zhang, Jingru Xiang, Qian Chang. Published by Nan Yang Academy of Sciences Pte. Ltd.

Creative Commons LicenseThis is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.


Abstract

The change of information scenario may change the market transaction cost of different factors, thus changing the relative price of factors and inducing the substitution of production factors, but there is no research to prove this. Therefore, this study takes labor-saving technology (mechanical substitution of labor) as an example, evaluates informatization from three aspects of information technology access, information technology application and information literacy comprehensively, and uses the probit model and CMP method to analyze whether informatization causes the substitution of agricultural machinery inputs for labor inputs and its heterogeneity. The results show that informatization has a significant negative impact on farmers' choice of labor-saving technology, and the result is robust at the regional level, but the negative impact of informatization on farmers' choice of labor-saving technology in the eastern region is smaller than that in the western region. The level of information literacy has the largest negative impact on farmers' choice of labor-saving technology, followed by the level of access to information technology, and the level of application of information technology has the smallest impact. The study concludes that informatization has not led to the significant substitution of labor by machinery in apple production. Thus, the results are important for enriching the theory of induced change in agricultural technology in the context of informatization.

Keywords: Information technology access, Information technology application, Information literacy, Labor-saving technology, Agricultural factor substitution


References

[1] Liu, Q., Shumway, C.R., 2006. Geographic aggregation and induced innovation in American agriculture. Applied Economics. 38(6), 671-682. DOI: https://doi.org/10.1080/00036840500397457

[2] Fan, S., 1991. Effects of technological change and institutional reform on production growth in Chinese agriculture. American Journal of Agricultural Economics. 73(2), 266-275. DOI: https://doi.org/10.2307/1242711

[3] Lin, J.Y., 1995. Endowments, technology, and factor markets: A natural experiment of induced institutional innovation from China’s rural reform. American Journal of Agricultural Economics. 77(2), 231-242. DOI: https://doi.org/10.2307/1243533

[4] Aker, J.C., Ghosh, I., Burrell, J., 2016. The promise (and pitfalls) of ICT for agriculture initiatives. Agricultural Economics. 47(S1), 35-48. DOI: https://doi.org/10.1111/agec.12301

[5] Mwakaje, A.G., 2010. Information and Communication Technology for Rural Farmers Market Access in Tanzania [Internet]. Available from: http://repository.costech.or.tz/handle/123456789/10718

[6] Al-Hassan, R.M., Egyir, I.S., Abakah, J., 2013. Farm household level impacts of information communication technology (ICT)-based agricultural market information in Ghana. Journal of Development and Agricultural Economics. 5(4), 161-167. DOI: https://doi.org/10.5897/JDAE12.143

[7] Hayami ,Y., Ruttan, V.W., 1971. Agricultural development: An international perspective. Johns Hopkins University Press: Baltimore. DOI: https://doi.org/10.2307/1242686

[8] Ren, W., Zeng, Q., 2021. Is the green technological progress bias of mariculture suitable for its factor endowment?—empirical results from 10 coastal provinces and cities in China. Marine Policy. 124, 104338. DOI: https://doi.org/10.1016/j.marpol.2020.104338

[9] Xin, X., Liu, X., 2008. Regional disparity of factor endowment and agricultural labor productivity in China. Frontiers of Economics in China. 3, 380-409. DOI: https://doi.org/10.1007/s11459-008-0018-4

[10] Zheng, X., Wang, F., Ying, R., 2018. Farmers’ endowment constraints, technical properties and agricultural technology selection preferences: An analytical framework of farmers’ technology adoption under an incomplete factor market. China Rural Economy. (3).

[11] Zheng, X.Y., Zhuang, L.J., 2018. Variable factors costs, farmers endowment and agricultural technique choice-analysis based on micro-data from main Chinese lychee production region. Journal of Southern Agriculture. 49(1), 178-184.

[12] Kung, J.K.S., Bai, Y., 2011. Induced institutional change or transaction costs? The economic logic of land reallocations in Chinese agriculture. Journal of Development Studies. 47(10), 1510-1528. DOI: https://doi.org/10.1080/00220388.2010.506916

[13] Zhang, S., Sun, Z., Ma, W., et al., 2020. The effect of cooperative membership on agricultural technology adoption in Sichuan, China. China Economic Review. 62, 101334. DOI: https://doi.org/10.1016/j.chieco.2019.101334

[14] Zheng, H., Ma, J., Yao, Z., et al., 2022. How does social embeddedness affect farmers’ adoption behavior of low-carbon agricultural technology? Evidence from Jiangsu Province, China. Frontiers in Environmental Science. 10, 909803. DOI: https://doi.org/10.3389/fenvs.2022.909803

[15] Zheng, Y.Y., Zhe, T.H., Jia, W., 2022. Does Internet use promote the adoption of agricultural technology? Evidence from 1 449 farm households in 14 Chinese provinces. Journal of Integrative Agriculture. 21(1), 282-292. DOI: https://doi.org/10.1016/S2095-3119(21)63750-4

[16] Luh, Y., Jiang, W., Chien, Y., 2014. Adoption of genetically-modified seeds in Taiwan: The role of information acquisition and knowledge accumulation. China Agricultural Economic Review. 6(4), 11-21. DOI: https://doi.org/10.1108/CAER-03-2013-0037

[17] Yue, S., Xue, Y., Lyu, J., et al., 2023. The effect of information acquisition ability on farmers’ agricultural productive service behavior: An empirical analysis of corn farmers in northeast China. Agriculture. 13(3), 573. DOI: https://doi.org/10.3390/agriculture13030573

[18] Zhang, Y., Wang, L., Duan, Y., 2016. Agricultural information dissemination using ICTs: A review and analysis of information dissemination models in China. Information Processing in Agriculture. 3(1), 17-29. DOI: https://doi.org/10.1016/j.inpa.2015.11.002

[19] Mwalupaso, G.E., Wang, S., Rahman, S., et al., 2019. Agricultural informatization and technical efficiency in maize production in Zambia. Sustainability. 11(8), 2451. DOI: https://doi.org/10.3390/su11082451

[20] Liu, C., 2016. Sustainability of rural informatization programs in developing countries: A case study of China’s Sichuan province. Telecommunications Policy. 40(7), 714-724. DOI: https://doi.org/10.1016/j.telpol.2015.08.007

[21] Zhang, X., Yang, F., 2019. Rural informatization policy evolution in China: A bibliometric study. Scientometrics. 120(1), 129-153. DOI: https://doi.org/10.1007/s11192-019-03105-z

[22] Churi, A.J., Mlozi, M.R., Tumbo, S.D., et al., 2012. Understanding Farmers Information Communication Strategies for Managing Climate Risks in Rural Semi-arid Areas, Tanzania [Internet]. Available from: https://www.suaire.sua.ac.tz/handle/123456789/3967

[23] Hasler, L., Ruthven, I., Buchanan, S., 2014. Using internet groups in situations of information poverty: Topics and information needs. Journal of the Association for Information Science and Technology. 65(1), 25-36. DOI: https://doi.org/10.1002/asi.22962

[24] Sang, N., Cheruiyot, J.K., 2020. Farmers’ Information Literacy and Productivity Performance of Smallholder Horticulture in a Highland Zone, Kenya [Internet]. Available from: http://ir-library.kabianga.ac.ke/handle/123456789/359

[25] Busindeli, I.M., 2016. Communication media preferences by rural communities for acquisition of agricultural information in Mvomero and Kilosa Districts, Morogoro, Tanzania [Ph.D. thesis]. Morogoro: Sokoine University of Agriculture.

[26] Catts, R., Lau, J., 2008. Towards Information Literacy Indicators [Internet]. Available from: http://hdl.handle.net/1893/2119

[27] Olmstead, A.L., Rhode, P., 1993. Induced innovation in American agriculture: A reconsideration. Journal of Political Economy. 101(1), 100-118. DOI: https://doi.org/10.1086/261867

[28] Gallardo, R.K., Sauer, J., 2018. Adoption of labor-saving technologies in agriculture. Annual Review of Resource Economics. 10, 185-206. DOI: https://doi.org/10.1146/annurev-resource-100517-023018

[29] Martha Jr, G.B., Alves, E., Contini, E., 2012. Land-saving approaches and beef production growth in Brazil. Agricultural Systems. 110, 173-177. DOI: https://doi.org/10.1016/j.agsy.2012.03.001

[30] Hayami, Y., Ruttan, V.W., 1970. Agricultural productivity differences among countries. American Economic Review. 60(5), 895-911.

[31] Dubois, D., Vukina, T., 2004. Grower risk aversion and the cost of moral hazard in livestock production contracts. American Journal of Agricultural Economics. 86(3),835-841.

[32] Sadoulet, E., de Janvry, A., 1995. Quantitative development policy analysis. Johns Hopkins University Press: Baltimore. DOI: https://doi.org/10.2307/1243800

[33] Key, N., Sadoulet, E., de Janvry, A., 2000. Transactions costs and agricultural household supply response. American Journal of Agricultural Economics. 82(2), 245-259. DOI: https://doi.org/10.1111/0002-9092.00022

[34] Zanello, G., 2012. Mobile phones and radios: Effects on transactions costs and market participation for households in Northern Ghana. Journal of Agricultural Economics. 63(3),694-714. DOI: https://doi.org/10.1111/j.1477-9552.2012.00352.x

[35] Muto, M., Yamano, T., 2009. The impact of mobile phone coverage expansion on market participation: Panel data evidence from Uganda. World Development. 37(12), 1887-1896. DOI: https://doi.org/10.1016/j.worlddev.2009.05.004

[36] Smithson, C.W., 1979. Relative factor usage in Canadian mining: Neoclassical substitution or biased technical change? Resources & Energy. 2(4), 373-389. DOI: https://doi.org/10.1016/0165-0572(79)90014-8

[37] Wang, J., Huo, X., Hatab, A.A., et al., 2012. Non-neutral technology, farmer income and poverty reduction: Evidence from high-value agricultural household in China. Journal of Food Agriculture and Environment. 10(3), 582-589.

[38] Olale, E., Cranfield, J.A.L., 2009. The Role of Income Diversification, Transaction Cost and Production Risk in Fertilizer Market Participation [Internet]. Available from: https://ageconsearch.umn.edu/record/49929

[39] Roodman, D., 2011. Fitting fully observed recursive mixed-process model with CMP. The Stata Journal. 29(2), 159-206. DOI: https://doi.org/10.1177/1536867X1101100202

[40] Agarwal, R., Animesh, A., Prasad, K., 2009. Research note—Social interactions and the “digital divide”: Explaining variations in internet use. Information Systems Research. 20(2), 277-294. DOI: https://doi.org/10.1287/isre.1080.0194

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