嘉兴星源广场停车场MNT评价模型分析数据

随着城市化进程的加快，汽车保有量急剧增加，停车场作为城市交通系统的重要组成部分，其经营与管理显得尤为关键。通过建立停车场MNT模型看清停车场的经营情况，从而指定不同的策略，提升城市交通环节运行效率。
一、提升场地规划与建设的科学性：通过停车场MNT模型，可以快速识别出价值较高和需要扶持的停车场，长期价值较高的停车场可扩大场地，满足市民出行需求并提升收入。长期价值较低停车场可适当缩减场地压降成本、增加充电车位提升差异化竞争优势。
二、提升低收费停车场经营收入：通过分析停车场0元收费占比，可对预警停车场采取一定措施如推荐包月包年等优惠策略，吸引客流提升经营收入。一、数据采集：原始数据来自公司业务采集数据，包含停车场名称、车牌号、出入场时间、停车费实收金额、状态等原始数据字段，并对车牌号等敏感信息进行加密处理。
二、算法规则：
通过比较本停车场和公司旗下所有停车场一段时间内平均收费金额、停车次数、平均停车时长数据，建立停车场MNT评价模型，并根据停车场0元收费占比进行预警。
1、车辆单次停车时长=出场时间-入场时间；
2、该停车场平均收费金额=该停车场停车费实收金额合计/停车次数，高于公司旗下所有停车场平均收费金额的赋M，否则赋m；
3、该停车场停车次数高于高于公司旗下所有停车场平均停车次数的赋N，否则赋n；
4、该停车场平均停车时长=该停车场停车时长合计/停车次数，高于公司旗下所有停车场平均停车市场的赋T，否则赋t；
5、再根据MNT模型分层规则，将停车场分为4个层级，分别为重要价值（MNT）、重要发展（mNT、MnT、MNt）、一般价值（Mnt、mNt、mnT）、重点扶持（mnt），不同层级指定不同的经营策略；
6、0元收费占比=该停车场停车费0元订单数（去除支付类型为包期）/总订单数，占比超85%进行预警，标记为需经营优化停车场。

With the accelerated pace of urbanization and the sharp increase in vehicle ownership, parking lots, as an important component of urban transportation systems, have become increasingly critical in terms of their operation and management. Establishing a parking lot MNT model can clarify the operational status of parking lots, thereby formulating differentiated strategies to improve the operational efficiency of urban transportation links.

1. Enhancing the scientific rigor of site planning and construction:
The parking lot MNT model can quickly identify parking lots with high long-term value and those in need of support. For parking lots with high long-term value, their site scale can be expanded to meet citizens' travel demands and increase revenue. For parking lots with low long-term value, the site scale can be appropriately downsized to reduce operational costs, and charging parking spaces can be added to enhance differentiated competitive advantages.

2. Improving operating revenue of low-fee parking lots:
By analyzing the proportion of zero-fee parking transactions in parking lots, targeted measures such as preferential policies including monthly/annual subscription recommendations can be adopted for early-warning parking lots to attract more traffic and improve operating revenue.

1. Data Collection:
The raw data comes from the company's operational collection data, including original data fields such as parking lot name, license plate number, entry and exit time, actual parking fee collected, status, etc. Sensitive information such as license plate numbers is encrypted.

2. Algorithm Rules:
The parking lot MNT evaluation model is established by comparing the average charging amount, number of parking sessions, and average parking duration of this parking lot and all parking lots under the company over a certain period of time, and early warnings are issued based on the proportion of zero-fee parking transactions.
1. Single parking duration = Exit time - Entry time;
2. Average charging amount of this parking lot = Total actual parking fees collected / Number of parking sessions. If the value is higher than the average charging amount of all parking lots under the company, assign value M; otherwise, assign value m;
3. Number of parking sessions of this parking lot: if higher than the average number of parking sessions of all parking lots under the company, assign value N; otherwise, assign value n;
4. Average parking duration of this parking lot = Total parking duration / Number of parking sessions. If higher than the average parking duration of all parking lots under the company, assign value T; otherwise, assign value t;
5. According to the hierarchical rules of the MNT model, parking lots are divided into 4 tiers: High Value (MNT), Developing High Potential (mNT, MnT, MNt), General Value (Mnt, mNt, mnT), and Key Support Target (mnt). Different operation strategies are formulated for different tiers;
6. Proportion of zero-fee transactions = Number of zero-fee parking orders (excluding subscription-based payments) / Total number of orders. If the proportion exceeds 85%, issue an early warning and mark it as a parking lot requiring operational optimization.

搜集汇总

数据集介绍

特点

该数据集为嘉兴星源广场停车场的经营数据，通过MNT评价模型分析停车场的经营情况，包含533条数据，每周更新。数据用于提升停车场规划与经营效率，特别是针对低收费停车场的收入优化。