Framework for Enhancing Park Service Effectiveness Leveraging Emerging Technologies

Highlights

	· Competing interests  The authors declare that they have no competing interests.
	· Accurately identifies park deficiency and provides recommendations through intelligent algorithms
	· Applies evaluation results into the workflow of park management strategies by knowledge graphs
	· Automatic report generation to enhance the efficiency of park service effectiveness evaluation
	· Utilizes LLM-based Q&A service for refined evaluation, diagnosis, and decision-making at a lower cost

Abstract

Effectively enhancing park service effectiveness is a pivotal pathway for advancing the construction of Park Cities. However, it has currently witnessed issues such as the misalignment between park management research and the actual deficiencies, a lack of connections from evaluation results to deficiency diagnosis and optimization recommendations, and the insufficiency in timeliness and continuity of research outcomes, which collectively fail to adequately support for park managers’ decision-making in service effectiveness enhancement. This study, addressing the entire workflow, proposes an “evaluation–diagnosis–decision-making” framework for the enhancement of park service effectiveness underpinned by new technologies. Initially, by leveraging multi-sourced data to expand the investigation dimensions of park service effectiveness, it conducts indicator evaluations with intelligent algorithms; subsequently, constructing knowledge graphs to achieve precise deficiency diagnosis and optimization recommendations; and finally, utilizing templates and intelligent technologies for automatic report generation, and introducing an intelligent question-and-answer service supported by the large language model, thereby offering refined evaluation, diagnosis, and decision-making assistance for enhancing park service effectiveness. With an empirical case study on the evaluation of park service effectiveness in Beijing, the article demonstrates the application effectiveness of this framework, which can provide a new perspective and an operational tool for the improvement of urban park management services.

Graphical abstract

Keywords

Park Service Effectiveness / Park Management / Management Decision-making / Multi-sourced Data / Knowledge Graph / Large Language Model

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