Tea is one of the most significant cash crops in developing countries. Tea cultivation plays a pivotal role in rural development and poverty reduction. Currently, tea plucking is very labour-intensive. In response to the challenges of rural labor reduction and labour cost control, mechanization is a strategy to reduce costs. However, it remains unclear whether mechanization is beneficial to tea owners. This paper utilises system dynamics to investigate this problem. First, the boundaries of the system were defined. Secondly, variables were identified to construct a causal loop diagram. The variables were then defined and categorized, after which the stock flow diagrams were constructed, and the system dynamics equations were developed. Finally, multiple scenario-based simulations were conducted. Three scenarios were explored namely labour-only, machinery-only, and combined scenarios. Within the constraints of the model, simulations can result in additional revenue from machinery. The simulation results are accurate within the defined boundaries of the model, while acknowledging for other possible variables not part of the model. Possible improvements and recommendations are presented at the end.

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Cost-Benefit Analysis and Technology Transition Management of Automation Adoption in Tea Plucking Based on System Dynamics Model Design

  • Ziyan Gao,
  • Andrew Huey Ping Tan,
  • Joe Lo Ying Tuan,
  • Yufan Zheng,
  • Yang Luo

摘要

Tea is one of the most significant cash crops in developing countries. Tea cultivation plays a pivotal role in rural development and poverty reduction. Currently, tea plucking is very labour-intensive. In response to the challenges of rural labor reduction and labour cost control, mechanization is a strategy to reduce costs. However, it remains unclear whether mechanization is beneficial to tea owners. This paper utilises system dynamics to investigate this problem. First, the boundaries of the system were defined. Secondly, variables were identified to construct a causal loop diagram. The variables were then defined and categorized, after which the stock flow diagrams were constructed, and the system dynamics equations were developed. Finally, multiple scenario-based simulations were conducted. Three scenarios were explored namely labour-only, machinery-only, and combined scenarios. Within the constraints of the model, simulations can result in additional revenue from machinery. The simulation results are accurate within the defined boundaries of the model, while acknowledging for other possible variables not part of the model. Possible improvements and recommendations are presented at the end.