Are small farms sustainable and technologically smart? Evidence from Poland, Romania, and Lithuania

IF 0.5 Q4 ECONOMICS
S. Stępień, K. Smędzik-Ambroży, J. Polcyn, A. Kwiliński, Ionut Maican
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引用次数: 2

Abstract

Abstract Sustainable development of farms is determined by many factors and, in recent years, significance of modern technologies and artificial intelligence (AI) has been pointed out, especially in terms of beneficial effects on economic performance and natural resources. Therefore, there is a need to answer the question about the application of AI technologies in small-scale farms, especially those with a relatively high level of sustainability. In order to obtain the information, a survey in Poland, Romania and Lithuania was carried out. Among the respondents, the 20 most sustainable farms in each country were selected using the CRITIC-TOPSIS method. Next, in-depth interviews were conducted to explore attitudes, behaviour and knowledge of AI.. The results show that small-scale farms in selected countries do not apply artificial intelligence. Although owners recognise and appreciate the benefits of AI, they are not convinced to implement this technology in their own business, they are not completely uncritical about using AI tools in the practice. The main obstacles are: low level of knowledge, misconception of the price of innovation or lack of capital for buying more advanced technology, low interest in implementing innovative solutions due the small scale of production or habituation to traditional production methods.
小农场是可持续的,技术上明智的吗?来自波兰、罗马尼亚和立陶宛的证据
农场的可持续发展是由许多因素决定的,近年来,现代技术和人工智能(AI)的意义已经被指出,特别是在经济效益和自然资源方面的有益影响。因此,有必要回答人工智能技术在小规模农场,特别是那些可持续性水平相对较高的农场中的应用问题。为了获得资料,在波兰、罗马尼亚和立陶宛进行了一项调查。在受访者中,使用critical - topsis方法选择了每个国家20个最可持续的农场。接下来,进行了深度访谈,以探索对人工智能的态度、行为和知识。结果显示,选定国家的小规模农场没有应用人工智能。虽然业主认识到并欣赏人工智能的好处,但他们不相信在自己的业务中实施这项技术,但他们对在实践中使用人工智能工具并非完全不加批判。主要障碍是:知识水平低,对创新价格的误解或缺乏购买更先进技术的资金,由于生产规模小或对传统生产方法的习惯,对实施创新解决方案的兴趣低。
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来源期刊
CiteScore
0.60
自引率
0.00%
发文量
9
期刊介绍: The Central European Journal of Economic Modelling and Econometrics (CEJEME) is a quarterly international journal. It aims to publish articles focusing on mathematical or statistical models in economic sciences. Papers covering the application of existing econometric techniques to a wide variety of problems in economics, in particular in macroeconomics and finance are welcome. Advanced empirical studies devoted to modelling and forecasting of Central and Eastern European economies are of particular interest. Any rigorous methods of statistical inference can be used and articles representing Bayesian econometrics are decidedly within the range of the Journal''s interests.
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