基于知信行理论的外卖配送员交通行为分析

吕慧; 姚晓霞; 王超; 李杰

doi:10.3963/j.jssn.1674-4861.2024.03.010

基于知信行理论的外卖配送员交通行为分析

doi: 10.3963/j.jssn.1674-4861.2024.03.010

吕慧^1,,
姚晓霞²,
王超^3, ,,
李杰⁴

1.
应急管理部宣传教育中心北京 100013
2.
长安大学经济与管理学院西安 710064
3.
山东大学威海前沿交叉科学院研究院山东威海 264209
4.
中国科学院文献情报中心北京 100190

基金项目:

山东省重点研发计划(软科学项目)重大项目 2023RZA02019

详细信息

作者简介:
吕慧(1986—)，硕士，高工. 研究方向：交通安全风险评估. E-mail: 569228194@qq.com

通讯作者:
王超(1984—)，博士，教授. 研究方向：交通运输经济与管理. E-mail: nihaochao6@163.com

中图分类号: X959
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- 被引次数: 0
出版历程
- 收稿日期: 2023-05-03
- 网络出版日期: 2024-10-21

A Traffic Behavior Analysis of Food Delivery Workers Based on Knowledge Attitude Belief Practice Model

LYU Hui^1
,,
YAO Xiaoxia²,
WANG Chao^{3
, ,},
LI Jie⁴

1.
Publicity and Education Center of Ministry of Emergency Management, Beijing 100013, China
2.
School of Economics and Management, Chang'an University, Xi'an 710064, China
3.
Institute for Interdisciplinary Research, Shandong University, Weihai 264209, Shandong, China
4.
National Science Library, Chinese Academy of Sciences, Beijing 100190, China

摘要

摘要: 为减少外卖配送员道路交通安全事故的发生，对传统知信行理论(knowledge, attitude/belief, practice，KAP)模型进行扩展，引入外卖配送员个体特征和劳动强度2个新变量，以1 610名外卖配送员的有效调查问卷为研究样本，通过对问卷量表进行Cronbach's α信度分析和KMO检验、Bartlett球形度检验效度分析，进行探索性因子分析后构建适用于外卖配送员群体的结构方程模型(structural equation modeling，SEM)，并对构建的模型进行适配度检验和路径系数检验。结果表明：外卖配送员的个体认知和主观态度对交通行为产生直接影响，影响系数为0.284和0.209；且个体认知还可通过主观态度，间接影响个体交通行为。外卖配送员个体的劳动强度对交通行为产生直接的负向影响，影响系数为－0.390，具体而言，劳动强度越大，外卖配送员个体的交通安全行为风险越大。同时，通过研究发现，劳动强度已成为引发外卖配送员交通安全事故的重要诱因，而外卖配送员的个体特征、主观态度则是劳动强度的主要影响因素。由于外卖配送员的个体特征存在差异，其个体认知、主观态度、劳动强度及交通行为也会有所不同。而平台企业对不安全交通行为的处罚措施，可以起到规范外卖配送员交通行为的期待效果，进而减少交通违规次数和交通事故的发生。此外，外卖配送员自身的交通安全意识不仅会影响个体交通行为表现，还会对周边外卖配送员的交通安全认知造成负外部影响，进而导致“羊群效应”的产生。
- 交通安全 /
- 外卖配送员 /
- 职业安全 /
- 知信行理论(KAP) /
- 负外部性
Abstract: In order to alleviate the occurrence of road traffic safety accidents in the process of food delivery, a structural equation model is constructed based on the extended theory of knowledge, attitude/belief, practice (KAP), and the effective questionnaires of 1 610 food delivery workers are taken as samples to quantize the influencing mechanism of factors such as individual characteristics, individual cognition, subjective attitude, labor intensity and traffic behavior of food delivery. A Cronbach's α coefficient reliability analysis is conducted on the questionnaire scale, and KMO test and Bartlett sphericity test are used to determine whether factor analysis can be performed. The exploratory factor analysis is carried out, and the principal factors are extracted by the method of feature root greater than 1. The maximum variance rotation method is used to make the factor variables more interpretable. The structural equation modeling (SEM) is used for studying the psychological attribution of traffic behavior, and the fit test and path coefficient test are carried out on the constructed model. The results show that the individual cognition and subjective attitude of food delivery workers directly influences the traffic behavior, The individual cognition and subjective attitude of the deliverymen directly affected their traffic behavior, and the influence coefficients are 0.284 and 0.209. Moreover, individual cognition can also indirectly affect their traffic behavior by affecting their subjective attitude. The labor intensity of individual distributors has a direct negative impact on traffic behavior and the influence coefficient is －0.390. Specifically, the greater the labor intensity, the greater the risk of traffic safety behavior of individual delivery workers. At the same time, the study found that labor intensity has become an important cause of traffic safety accidents of delivery workers, and the individual characteristics and subjective attitude of delivery workers are the main influencing factors of labor intensity. Due to the differences in individual characteristics of delivery workers, their individual cognition, subjective attitude, labor intensity and traffic behavior will also be different. The punishment measures for enterprises of unsafe traffic behaviors can play the expected effect of standardizing the traffic behaviors of delivery workers, thus reducing the number of traffic violations and the occurrence of traffic accidents. In addition, the traffic safety awareness of the delivery workers themselves will not only affect the individual traffic behavior performance, but also have a negative external impact on the traffic safety cognition of the surrounding delivery workers, which leads to the"herding effect".
- traffic safety /
- food delivery worker /
- occupational safety /
- KAP theory /
- negative externality

HTML全文

图 1 理论模型

Figure 1. Theoretical model

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图 2 个体安全意识的负外部性分析

Figure 2. The analysis of negative externalities of individual safety consciousness

下载: 全尺寸图片幻灯片

表 1 研究假设

Table 1. Research assumptions

序号	假设内容
假设1：	H1a: 个体特征对个体认知有显著影响
	H1b: 个体特征对主观态度有显著影响
	H1c: 个体特征对劳动强度有显著影响
	H1d: 个体特征对交通行为有显著影响
假设2：	H2a: 个体认知对主观态度有正相关
假设2：	H2b: 个体认知对交通行为有正相关
假设3：	H3a: 主观态度对劳动强度有负相关
假设3：	H3b: 主观态度对交通行为有正相关
假设4：	H4:劳动强度对交通行为有负相关

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表 2 测量成分

Table 2. Measurements

变量属性	测量项目	题项
	年龄/岁	TZ1
个体特征	文化程度	TZ2
	婚育状况	TZ3
	每日工作时长/h	QD1
劳动强度	每日送单量/单	QD2
	每日配送公里数/km	QD3
个体认知	我认为外卖平台企业关心配送员交通安全	RZ1
	我认为外卖平台企业会对配送员进行安全培训	RZ2
	我认为外卖配送同行安全意识普遍较高	RZ3
	我会留意信号灯、标志标牌等交通安全信息	TD1
主观态度	安全教育培训对我很重要	TD2
主观态度	同行的安全意识对我影响很大	TD3
	外卖平台企业对不安全交通行为的处罚能够规范我的交通行为	TD4
交通行为	外卖配送骑行速度	XW1
交通行为	外卖配送时经常发生交通事故	XW2

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表 3 KMO和Bartlett检验

Table 3. KMO and Bartlett's test

KMO检验	Bartlett球形度检验
KMO检验	近似卡方	自由度	显著性
0.769	4 860.307	66.000	0.000***
注：***为1%的显著性水平。

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表 4 总方差解释

Table 4. Total variance analysis

成分	特征根	方差解释率/%	累积百分比/%	特征根	旋转后方差解释率/%	旋转后累积百分比/%
1	3.256	27.1	27.1	2.760	23.0	23.0
2	2.021	16.8	44.0	1.931	16.1	39.1
3	1.314	10.9	54.9	1.605	13.4	52.5
4	0.957	8.0	62.9	1.252	10.4	62.9
5	0.866	7.2	70.1
6	0.747	6.2	76.3
7	0.676	5.6	82.0
8	0.570	4.8	86.7
9	0.488	4.1	90.8
10	0.448	3.7	94.5
11	0.358	3.0	97.5
12	0.300	2.5	100.0

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表 5 旋转后的因子载荷矩阵

Table 5. Rotated component matrix

问项	因子1	因子2	因子3	因子4	共同度
每日工作时长	0.002	0.816	0.048	-0.03	0.669
每日送单量	0.016	0.814	0.014	0.035	0.664
每日配送公里数	0.047	0.742	0.119	0.167	0.595
外卖平台企业对不安全交通行为的处罚能够规范我的交通行为	0.617	0.066	0.154	0.008	0.409
我会留意信号灯、标志标牌等交通安全信息	0.793	0.006	0.193	0.126	0.682
安全教育培训对我很重要	0.775	－0.04	0.243	0.134	0.679
同行的安全意识对我影响很大	0.783	0.046	0.038	0.038	0.618
我认为外卖平台企业会对配送员进行安全培训	0.154	0.016	0.844	0.105	0.747
我认为外卖平台企业关心配送员交通安全	0.422	0.111	0.733	0.106	0.738
我认为外卖配送同行安全意识普遍较高	0.565	0.037	0.431	0.061	0.51
外卖配送时经常发生交通事故	0.118	0.029	0.000	0.824	0.693
外卖配送骑行速度	0.032	－0.17	0.181	0.694	0.545

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表 6 结构方程模型拟合指数

Table 6. Fitting index of the SEM

统计检验量	适配标准	结果	适配度判断
GFI	> 0.9	0.957	√
AGFI	> 0.9	0.936	√
CFI	> 0.9	0.918	√
RMSEA	< 0.08	0.060	√

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表 7 路径检验结果

Table 7. The result of the path test

路径关系	标准化路径系数	P值	假设结果
个体特征→个体认知	－0.059	0.043	成立
个体特征→主观态度	0.077	0.013	成立
个体特征→劳动强度	0.134	0.000	成立
个体特征→交通行为	0.108	0.022	成立
个体认知→主观态度	0.543	0.000	成立
个体认知→交通行为	0.284	0.000	成立
主观态度→劳动强度	－0.074	0.023	成立
主观态度→交通行为	0.209	0.000	成立
劳动强度→交通行为	－0.390	0.000	成立

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