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The application of new information technologies such as the Internet of Things (IoT) has caused a deep impact on production and operations management in various fields. In this paper, a mixed-integer programming model is proposed to generate integrative decision-making in the IoT-enabled fresh agri-products supply chains. The designed model integrates three key stages, that is, planting, storage, and distribution, to help growers make the optimal decisions for maximising revenue. Decisions are made after comprehensive consideration of market factors such as price and demand as well as agricultural characteristics such as crop yield and shelf life. Results of numerical experiments show that significant improvement of benefits can be obtained through the overall decision-making of planting, storage, and distribution. Additionally, it may be most beneficial for growers to keep the warehouse's storage time and storage capacity at a medium level. The IoT-based integrative decision-making method explored in this study can be applied to other fields including manufacturing to achieve more efficient production and operations management. [ABSTRACT FROM AUTHOR]

The digital capabilities driven by Internet of Things and affiliated techniques have enabled the prevailing service-oriented business models, among which servitization has been well recognised as one of the most competitive strategies for manufacturing companies. However, manufacturing companies usually show a lack of knowledge regarding the service offering associated to their manufactured products. Acquiring external knowledge from service providers is one effective way to tackle this problem, but due to the information asymmetry, the process of knowledge sharing between the two is often faced with a prisoner's dilemma game. Meanwhile, the company's game strategy will change with the evolution of the knowledge sharing network structure. We therefore consider the influence of group spatial structure on individual game strategy, marry a canonical evolutionary game model on the decision-making mechanism of individuals to the complex network theory on the interaction behaviour among individuals in the groups. By analysing the model, we reveal the influence of various factors under the dimensions of ability and benefit on the willingness of companies to share knowledge. We also demonstrate the divergence in the influence of various factors on different types of companies. [ABSTRACT FROM AUTHOR]

Agricultural scale management is an important means of improving agricultural production efficiency. To answer the controversy over whether different agricultural scale management models can improve production efficiency, this paper obtained 117,627 samples from 68 domestic and foreign literature and used meta-analysis to study the effects of land-scale operation (LSO) and service-scale operation (SSO) on agricultural production efficiency (APE). The moderators that affect the relationship between LSO, SSO, and APE are also examined. The research results show that (1) both LSO and SSO positively impact production efficiency, but LSO has a stronger impact. (2) The relationship between LSO and APE is positively regulated by the agricultural production and operation environment, characteristics of the agricultural location, degree of farmers' participation, and types of APE, and negatively regulated by the research situation. (3) The relationship between SSO and APE is negatively regulated by APE types and data types. Therefore, the government should promote agricultural dual-scale operation according to the local conditions through the complementary advantages of LSO and SSO, so as to fully release the promotion potential of APE. [ABSTRACT FROM AUTHOR]