This page has only limited features, please log in for full access.
Central and East European (CEE) countries are attractive among emerging markets due to a combination of factors such as economic growth and market potential. Although the CEE countries as a whole have a very high degree of connectivity, each country has different market opportunities and external environment, so agricultural enterprises wanting to enter the CEE market must take into account the diverse and complex resource base of CEE countries. In the light of economic globalization, China and CEE countries face mutual opportunities and challenges, and it is necessary to strengthen agricultural cooperation. The potential of agricultural investment cooperation between China and CEE countries is the basis for multinational enterprises to allocate resources and implement internationalization strategies rationally. The purpose of this paper is to analyze theagricultural cooperation potential between China and CEE countries in the perspective of resource complementarity, with a selection of macro data related to agricultural capacity from 2009–2018. In particular, this study examines the differences and complementarities between China and CEE countries in terms of agricultural resource conditions and product output and trade; by constructing an agricultural cooperation potential evaluation model, the entropy value method is applied to predict and evaluate the potential characteristics of agricultural cooperation between China and CEE countries in 2021–2025. The research results show that the current intermittent and episodic nature of agricultural cooperation between China and CEE countries does not match the high or medium-high level of complementarity between agricultural production factors. Thus, agricultural enterprises can utiliza such considerable cooperation potential based on the resource complementarity to develop internationalization strategies and overseas investment.
Ru Guo; Xiaodong Qiu; Yiyi He. Research on Agricultural Cooperation Potential between China and CEE Countries Based on Resource Complementarity. Mathematics 2021, 9, 503 .
AMA StyleRu Guo, Xiaodong Qiu, Yiyi He. Research on Agricultural Cooperation Potential between China and CEE Countries Based on Resource Complementarity. Mathematics. 2021; 9 (5):503.
Chicago/Turabian StyleRu Guo; Xiaodong Qiu; Yiyi He. 2021. "Research on Agricultural Cooperation Potential between China and CEE Countries Based on Resource Complementarity." Mathematics 9, no. 5: 503.
Evaluation of agricultural investment climate has essential reference value for site selection, operation and risk management of agricultural outward foreign direct investment projects. This study builds a back propagation neural network-based agricultural investment climate evaluation model, which has 22 indicators of four subsystems that take political climate, economic climate, social climate, and technological climate as the input vector, and agricultural investment climate rating as the output vector, to evaluate the agricultural investment climate in 16 Central and Eastern European (CEE) countries. The overall spatial distribution characteristics demonstrate that the best agricultural investment climate is in the three Baltic countries, followed by the Visegrad Group and Slovenia sector, and then the Balkan littoral countries. The findings may provide insights for entrepreneurs who aim to invest in agriculture abroad and contribute to the improvement of these countries’ investment climate.
Ru Guo; Xiaodong Qiu; Yiyi He. Evaluation of Agricultural Investment Climate in CEE Countries: The Application of Back Propagation Neural Network. Algorithms 2020, 13, 336 .
AMA StyleRu Guo, Xiaodong Qiu, Yiyi He. Evaluation of Agricultural Investment Climate in CEE Countries: The Application of Back Propagation Neural Network. Algorithms. 2020; 13 (12):336.
Chicago/Turabian StyleRu Guo; Xiaodong Qiu; Yiyi He. 2020. "Evaluation of Agricultural Investment Climate in CEE Countries: The Application of Back Propagation Neural Network." Algorithms 13, no. 12: 336.